Abstract: In one aspect, a method, includes producing a centralness metric that is highest at a center of detail from a set of pixels and having a negative slope to neighboring pixels from a center pixel at the center of detail, calculating a delta signal for the set of pixels using the produced centralness metric and pixel values of the set of pixels, generating a squeezed pixel value for each of the pixel values of the set of pixels, and outputting the generated squeezed pixel values.

Abstract: A display method comprises: acquiring multiple frames of images to be displayed, one frame of two adjacent frames of the images to be displayed being an image in an odd-numbered row, the other frame being an image in an even-numbered row, the resolution of the image in the odd-numbered row being M*(a*N), the resolution of the image in the even-numbered row being M*(a*N) or (M?1)*(a*N), and a being 1 or 2; and causing an odd-numbered display group to display the image in the odd-numbered row, and causing an even-numbered display group to display the image in the even-numbered row, the odd-numbered display group comprising M*(a*N) odd-numbered display units, the even-numbered display group comprising (M?1)*(a*N) even-numbered display units, the odd-numbered display unit in the i-th row comprising a first sub-pixel, a second sub-pixel, and a third sub-pixel in a pixel unit in the i-th row.

Abstract: An image decoding method performed by a decoding apparatus according to the present document comprises the steps of: determining that a merge with motion vector difference (MMVD) mode has been applied to a current block that is a current picture referencing (CPR) coding block referring to a current picture; deriving a base motion information candidate for the current block on the basis of candidate blocks neighboring the current block; generating prediction samples for the current block on the basis of the base motion information candidate; and generating reconstruction samples for the current block on the basis of the prediction samples, wherein the base motion information candidate is derived depending on whether the neighboring candidate blocks are CPR coding blocks.

Abstract: Disclosed is an image encoding method. The method includes deriving a motion refinement candidate from among motion information of spatial neighboring blocks, motion information of a temporal neighboring blocks, predefined motion information, and motion information that most frequently occurs in a reference picture, performing a motion information refinement on the derived motion refinement candidate, and generating a prediction block of a current block by using the motion refinement candidate having undergone the motion information refinement.

Abstract: Techniques are disclosed for coding video data in which frames from a video source are partitioned into a plurality of tiles of common size, and the tiles are coded as a virtual video sequence according to motion-compensated prediction, each tile treated as having respective temporal location of the virtual video sequence. The coding scheme permits relative allocation of coding resources to tiles that are likely to have greater significance in a video coding session, which may lead to certain tiles that have low complexity or low motion content to be skipped during coding of the tiles for select source frames. Moreover, coding of the tiles may be ordered to achieve low coding latencies during a coding session.

Abstract: Several methods and systems for estimating motion in a plurality of multimedia pictures are disclosed. In an embodiment, at least one temporal distance between a multimedia picture and one or more reference pictures corresponding to the multimedia picture in a capture order associated with the plurality of multimedia pictures is computed. The at least one temporal distance is computed subsequent to an encoding of the multimedia picture. At least one motion estimation parameter is determined based on the at least one temporal distance. Motion associated with a subsequent multimedia picture to be encoded is estimated based on the at least one motion estimation parameter.

Abstract: A semiconductor device includes a core output driver, a pad input driver, and an arithmetic result data generation circuit. The core output driver transmits a first data, output from a core region, to a global input/output (I/O) line when an arithmetic operation is performed. The pad input driver transmits a second data, input through a pad region, to the global I/O line when the arithmetic operation is performed. The arithmetic result data generation circuit sequentially receives the first data and the second data through the global I/O line, to generate a core data and a pad data. The arithmetic result data generation circuit also performs an arithmetic operation, used in a neural network, based on the core data and the pad data, to generate arithmetic data.

Abstract: Techniques for psychovisually optimized dithering for image and video (e.g., frame) encoding are described. According to some embodiments, a computer-implemented method includes receiving a request to encode a video from a first depth of pixel values to a second, different depth of pixel values at a content delivery service, detecting a flat region without texturing and a non-flat region with texturing in a first frame of the video having the first depth of pixel values, dithering pixel values in the non-flat region and flattening pixel values in the flat region, encoding the dithered pixel values and the flattened pixel values of the frame into a first encoded frame having the second, different depth of pixel values by the content delivery service, and transmitting the first encoded frame from the content delivery service to a viewer device.

Abstract: A high-bandwidth memory (HBM) includes a memory and a controller. The controller receives a data write request from a processor external to the HBM and the controller stores an entry in the memory indicating at least one address of data of the data write request and generates an indication that a data bus is available for an operation during a cycle time of the data write request based on the data write request comprising sparse data or data-value similarity. Sparse data includes a predetermined percentage of data values equal to zero, and data-value similarity includes a predetermined amount of spatial value locality of the data values. The predetermined percentage of data values equal to zero of sparse data and the predetermined amount of spatial value locality of the special-value pattern are both based on a predetermined data granularity.

Abstract: The present disclosure relates to motion vector refinement. As a first step, an initial motion vector and a template for the block are obtained. Then, the refinement of the initial motion vector is determined by template matching with said template in a search space. The search space is located on a position given by the initial motion vector and includes one or more fractional sample positions, wherein each of the fractional sample positions belonging to the search space is obtained by interpolation filtering with a filter of a predefined tap-size assessing integer samples only within a window, said window being formed by integer samples accessible for the template matching in said search space.

Abstract: A method and a device for encoding or decoding video data. It concerns more particularly the encoding according to a particular encoding mode using a decoder side motion vector derivation mode referenced as frame-rate up conversion mode or FRUC mode. In FRUC merge mode, the derivation process comprises a refinement step to increase the accuracy of the obtained motion vector at the sub-pixel level. This process involves the evaluation of different sub-pixel position around the obtained motion vector according to different patterns. The present invention has been devised to improve the known refinement step. It aims at improving the coding efficiency by considering the characteristics of the matching type and/or the signal inside the templates.

Abstract: The present invention provides an image encoding method and an image decoding method. An image decoding method according to the present invention, for decoding an image by decoder-side motion information derivation, comprises the steps of: checking, from among a plurality of motion information derivation types, the motion information derivation type applied to the current block: and deriving motion information of the current block according to the checked motion information derivation type, wherein different motion information compensation techniques are applicable according to the motion information derivation type.

Abstract: An information processing device (100) extracts a first point group constituting an object from a first distance image acquired by a first sensor. The information processing device (100) extracts a second point group constituting an object from a second distance image acquired by a second sensor. The information processing device (100) generates a first translated point group by translating the first point group by first translation coordinates. The information processing device (100) generates a second translated point group by translating the second point group by second translation coordinates. The information processing device (100) calculates a rotation parameter and a translation parameter based on the first translated point group and the second translated point group.

Abstract: Aspects of the disclosure provide a method and an apparatus for video coding. In some examples, an apparatus includes processing circuitry that determines a plurality of first sub-block motion vectors for a plurality of sub-blocks of a current block, and determines a plurality of second sub-block motion vectors according to the plurality of first sub-block motion vectors and a first target range. The processing circuitry also determines a set of gradient values associated with a current sample location in a current sub-block, determines an adjustment vector associated with the current sample location, and determines a set of adjustment values associated with the current sample location according to the set of gradient values and the adjustment vector. The processing circuitry generates a predicted sample associated with the current sample location according to a combination of a corresponding sample in a reference sub-block and the set of adjustment values.

Abstract: The present invention relates to a method for encoding and decoding an image. The method for decoding an image includes: deriving an initial motion vector from a merge candidate list of a current block; deriving a refined motion vector using the initial motion vector; and generating a prediction block of the current block using the refined motion vector.

Abstract: The present disclosure relates to a signal processing device and an image display apparatus including the same. A signal processing device according to an embodiment of the present disclosure includes: an input interface to receive an image signal; a first image processor to generate first image frame data based on the image signal; a second image processor to generate second image frame data scaled down from the first image frame data based on the image signal; and an output interface to receive the first image frame data from the first image processor and the second image frame data from the second image processor and to output the first image frame data and the second image frame data, wherein the first image frame data output from the output interface is more delayed than the second image frame data output from the output interface. Accordingly, a timing controller may accurately and rapidly perform signal processing for a panel.

Abstract: A method includes obtaining a first motion vector of a motion compensation unit included in an affine code block. The method also includes determining a second motion vector based on the first motion vector, where a precision of the second motion vector matches a motion vector precision of a storage unit corresponding to the motion compensation unit. The method further includes determining a third motion vector based on the second motion vector, where there is a preset correspondence between the third motion vector and the second motion vector, and the third motion vector is used for subsequent encoding/decoding processing.

Abstract: A camera system may automatically identify high frequency motion regions in a field of view of the camera system. Analysis of motion events detected at different regions of a scene in the field of view, may be performed. Similar events frequently occurring at a certain region may be recorded/accumulated and compared to a threshold. Regions with high frequency activity may be determined and a user may be notified. If the user is not interested in events within the high activity regions, the regions may be ignored and notifications to the user may cease. The camera system may determine specific actions/events occurring in a region, such as a person approaching or leaving a home.

Abstract: An inter prediction method includes parsing, by a processor, a bitstream to obtain a location of a target adjacent image block of a current image block. The method further includes obtaining a preset correspondence between an adjacent image block location and a motion vector precision, wherein in the preset correspondence, locations of at least two adjacent image blocks correspond to different motion vector precisions. The method further includes determining, based on the location of the target adjacent image block and the preset correspondence, a target motion vector precision corresponding to the target adjacent image block. The method further includes determining a motion vector predictor of the current image block based on the location of the target adjacent image block and the target motion vector precision.

Abstract: An apparatus for generating a sound field description having a representation of sound field components, including a direction determiner for determining one or more sound directions for each time-frequency tile of a plurality of time-frequency tiles of a plurality of microphone signals; a spatial basis function evaluator for evaluating, for each time-frequency tile of the plurality of time-frequency tiles, one or more spatial basis functions using the one or more sound directions; and a sound field component calculator for calculating, for each time-frequency tile of the plurality of time-frequency tiles, one or more sound field components corresponding to the one or more spatial basis functions evaluated using the one or more sound directions and a reference signal for a corresponding time-frequency tile, the reference signal being derived from one or more microphone signals of the plurality of microphone signals.

Abstract: A multimodal remote sensing image matching method and system integrate different local feature descriptors for automatic matching of multimodal remote sensing images. First, a local feature descriptor, such as the Histogram of Oriented Gradient (HOG), the local self-similarity (LSS), or the Speeded-Up Robust Feature (SURF), is extracted for each pixel of an image to form a pixel-wise feature representation map. Then, the three-dimensional Fourier transform (namely 3D FFT) is used to establish a fast matching similarity metric in a frequency domain based on the feature representation map, followed by a template matching scheme to achieve control points (CP) between images. In addition, the novel pixel-wise feature representation technique named channel features of orientated gradients (CFOG), which outperforms the pixel-wise feature representation methods based on the traditional local descriptors (e.g., HOG, LSS and SURF) in both matching performance and computational efficiency.

Abstract: A method for motion estimation is provided that includes determining a first motion vector for a first child coding unit (CU) of a parent CU and a second motion vector for a second child CU of the parent CU, wherein the first child CU, the second child CU, and the parent CU are in a CU hierarchy, wherein the first and second child CUs are smallest size CUs in the CU hierarchy, and wherein a first motion search type is used to determine the first motion vector and the second motion vector, selecting the first and second motion vectors as candidate predictors for the parent CU, selecting a predictor for a prediction unit (PU) of the first parent CU from the candidate predictors, and refining the predictor using a second motion search type to determine a motion vector for the PU.

Abstract: A system comprises a source block buffer and a plurality of hardware motion estimation search processing units in communication with the source block buffer. The source block buffer is configured to store at least a portion of a source block of a source frame of a video. The plurality of hardware motion estimation search processing units are configured to perform at least a portion of a motion estimation for the source block at least in part in parallel across a plurality of different reference frames of the video. Each of the hardware motion estimation search processing units is configured to be assigned a different one of the plurality of different reference frames and is configured to compare at least the portion of the source block with a portion of the assigned one of the different reference frames.

Abstract: A method of performing adjustment of a convergence speed for an imaging parameter is based on detecting a motion of a selected face in a sequence of image frames. When the detected motion meets predefined motion criteria, a motion vector corresponding to the characterized motion of the face is computed. A value for a convergence adjustment factor for adjusting a convergence speed of an imaging parameter of the camera is determined based on the computed motion vector. The convergence speed of the imaging parameter of the camera is adjusted based on the determined value of the convergence adjustment factor.

Abstract: Systems and methods are disclosed for denoising chrominance channels of images. For example, methods may include receiving an image from one or more image sensors; determining a set of weights for the image based on a luminance channel of the image, wherein a weight in the set of weights corresponds to a subject pixel and a candidate pixel and is determined based on luminance values of one or more pixels of the image centered at the subject pixel and one or more pixels of the image centered at the candidate pixel; applying the set of weights to chrominance channels of the image to obtain a denoised image, wherein the subject pixel of the denoised image is determined based on the weight multiplied by the candidate pixel of the image; and storing, displaying, or transmitting an output image based on the denoised image.

Abstract: A load in processing of searching for a motion vector is reduced. In order to solve the problem described above, a motion vector derivation apparatus (3032, 3036 to 3038) according to one aspect of the present invention that derives a motion vector to be referred to for generating a prediction image to be used for coding or decoding of a video includes a motion vector search unit (30373) configured to search for a motion vector on a prediction unit basis through matching processing. The motion vector search unit (30373) is configured to stop search of the motion vector, depending on whether or not a conditional expression according to a pixel bit-depth is satisfied.

Abstract: Motion windows are generated from a query activity sequence. For each of the motion windows in the query activity sequence, a corresponding motion window in the reference activity sequence is found. One or more difference calculations are performed between the motion windows of the query activity sequence and the corresponding motion windows in the reference activity sequence based on at least one criterion associated with physical meaning. Abnormality of the motion windows is determined based on the one or more difference calculations. A standardized evaluation result of the query activity sequence is output based on the detected abnormal motion windows in the query activity sequence.

Abstract: A moving picture coding apparatus includes a co-located block information determination unit which determines which one of a forward reference block and a backward reference block will be a co-located block and further determines whether only the unidirectional motion vector of the motion vectors of the co-located block is to be stored in a colPic memory; a temporal motion vector predictor calculation unit which derives a candidate motion vector predictor in temporal motion vector predictor mode using the colPic information stored in the colPic memory; and an inter prediction control unit which determines to code a motion vector using a candidate motion vector predictor having least error from the motion vector derived by motion estimation among candidate motion vector predictors.

Abstract: A difference image representing intensity differences between a first medical image and a second medical image is generated. A mixture model is fitted to an intensity distribution of the difference image to identify a plurality of probability distributions which collectively model the intensity distribution. A plurality of intensity ranges is determined as a function of the plurality of probability distributions. Image data of the difference image is labeled by determining into which of the plurality of intensity ranges said labeled image data falls. This technique more accurately details changes in medical images than known systems and methods.

Abstract: A system and method for identifying presence of digital ghosting artifacts in videos is disclosed. The method comprises estimating a blending parameter (?) for a current image using a previous image and a next image of a digital video stream. Successively, a blended image (B) is created by mixing contents of the previous image and the next image based on the estimated blending parameter (?). Thereafter, a first similarity is computed between the blended image (B) and a de-interlaced image (C), based on a Normalized Cross Correlation (NCC) between multiple blocks of the blended image (B) and the de-interlaced image (C). Successively, a second similarity is computed between the blended image (B) and the de-interlaced image (C), based on values of standard deviation of an absolute difference frame determined between the blended image (B) and the de-interlaced image (C).

Abstract: Examples of techniques for adaptive object recognition for a target visual domain given a generic machine learning model are provided. According to one or more embodiments of the present invention, a computer-implemented method for adaptive object recognition for a target visual domain given a generic machine learning model includes creating, by a processing device, an adapted model and identifying classes of the target visual domain using the generic machine learning model. The method further includes creating, by the processing device, a domain-constrained machine learning model based at least in part on the generic machine learning model such that the domain-constrained machine learning model is restricted to recognize only the identified classes of the target visual domain. The method further includes computing, by the processing device, a recognition result based at least in part on combining predictions of the domain-constrained machine learning model and the adapted model.

Abstract: A degradation detection device (10) includes: an image acquisition unit (11) that acquires an image sequence of a detection target; a matching point specification unit (12) that specifies matching points in the image sequence; a motion amount calculation unit (13) that, based on the specified matching points, for each frame that constitutes the image sequence, specifies motion occurring between the frame and a frame immediately previous thereto, and calculates a motion amount for each of the matching points along a time series; and a degraded region candidate specification unit (14) that specifies a region in which degradation has likely occurred in the image sequence, based on the motion amounts of the matching points that were calculated along the time series.

Abstract: Technologies are disclosed for efficiently identifying objects in videos using deep neural networks and motion information. Using the disclosed technologies, the amount of time required to identify objects in videos can be greatly reduced. Motion information for a video, such as motion vectors, are extracted during the encoding or decoding of the video. The motion information is used to determine whether there is sufficient motion between frames of the video to warrant performing object detection on the frames. If there is insufficient movement from one frame to a subsequent frame, the subsequent frame will not be processed to identify objects contained therein. In this way, object detection will not be performed on video frames that have changed minimally as compared to a previous frame, thereby reducing the amount of time and the number of processing operations required to identify the objects in the video.

Abstract: Examples are provided for apparatus and methods for video encoding and decoding. An encoder apparatus for encoding a picture into a data stream is configured to: subject a transform of a block of the picture to quantization to obtain a quantized transform; determine a zero-quantized portion of the quantized transform; determine at least one noise parameter providing noise information on the transform within the zero-quantized portion; signal the quantized transform and the at least one parameter.

Abstract: A wireless mesh network and a method of reducing for reducing a sampling rate of a streaming protocol in a multi-hop mesh network is disclosed. The method comprising: receiving, by a source node in the mesh network, an input data stream; generating, by the source node, a plurality of sample frames from the received input data stream, each of the plurality of sample frames having a sample rate that can be handled by the mesh network, transmitting the plurality of the sample frames to one or more sink nodes and reconstructing the input data stream from the plurality of sample frames received at the one or more sink nodes. The input data stream may be received from an application outside the mesh network or from an application in the source node. The reconstruction may use interpolation, which may be dynamically varied, and may be informed by metadata transmitted from the original source node.

Abstract: A method for encoding an image having been cut up into partitions. The method includes: predicting data of a current partition based on an already encoded and then decoded reference partition, generating a predicted partition; determining residual data by comparing data relating to the current partition with the predicted partition, the residual data associated with various digital data items. Prior producing a signal containing the encoded information, performing the following steps: determining, from the predetermined residual data, a subset containing residual data capable of being modified; calculating the value of a function representative of the residual data; comparing the calculated value with a value of at least one of the digital data items; based on the comparison, modification or non-modification of at least one of the residual data items of the subset; and, in the event of a modification, entropy encoding the at least one modified residual data item.

Abstract: An encoder includes circuitry and memory connected to the circuitry. The circuitry, in operation: derives, as a first parameter, a total sum of absolute values of sums of horizontal gradient values respectively for pairs of relative pixel positions; derives, as a second parameter, a total sum of absolute values of sums of vertical gradient values respectively for the pairs of relative pixel positions; derives, as a third parameter, a total sum of horizontal-related pixel difference values respectively for the pairs of relative pixel positions; derives, as a fourth parameter, a total sum of vertical-related pixel difference values respectively for the pairs of relative pixel positions; derives, as a fifth parameter, a total sum of vertical-related sums of horizontal gradient values respectively for the pairs of relative pixel positions; and generates a prediction image to be used to encode the current block using the first, second, third, fourth, and fifth parameters.

Abstract: The systems and methods provided herein are directed to automatically capturing, curating, and sharing recordings of a user. The automated recording and sharing features are designed to adapt to user preferences based on a history of what the user has chosen to record and share previously.

Abstract: An example device for coding video data may include a memory configured to store a current block of the video data and one or more processors implemented in circuitry coupled to the memory. The one or more processor may be configured to determine delta motion vectors from control point motion vectors of a neighboring block of a current block. The one or more processors may also be configured to clip the delta motion vectors to a predefined range. The one or more processors may also be configured to code the current block of video data using the clipped delta motion vectors.

Abstract: A video decoder selects a source affine block. The source affine block is an affine-coded block that spatially neighbors a current block. Additionally, the video decoder extrapolates motion vectors of control points of the source affine block to determine motion vector predictors for control points of the current block. The video decoder inserts, into an affine motion vector predictor (MVP) set candidate list, an affine MVP set that includes the motion vector predictors for the control points of the current block. The video decoder also determines, based on an index signaled in a bitstream, a selected affine MVP set in the affine MVP set candidate list. The video decoder obtains, from the bitstream, motion vector differences (MVDs) that indicate differences between motion vectors of the control points of the current block and motion vector predictors in the selected affine MVP set.

Abstract: Systems and methods are provided herein for minimizing obstruction of a media asset by an overlay by predicting a path of movement of an object of interest of the media asset and avoiding placement of the overlay in the path of movement. To this end, a media guidance application may detect an object of interest in a first frame of a media asset, and may determine a determining a first location of the object in the first frame and a second location of the object of interest in a second frame. The media guidance application may calculate, based on the first location and the second location, a projected location of the object of interest in a third frame of the media asset, and may generate for display an overlay in a location that does not overlap with any of the first location, the second location, and the projected location.

Abstract: The present invention relates to an image processing apparatus, an image processing method, and a recording medium for recording the same, the image processing apparatus including a storage configured to comprise a standard database (DB) established based on information about a predetermined anatomical entity; and at least one processor configured to obtain a local motion vector by registration between a first medical image and a second medical image taken by scanning an object including the anatomical entity, use a predictive local motion vector generated from the standard DB to normalize the local motion vector according to a plurality of regions in the anatomical entity, and make information about conditions of the anatomical entity based on the normalized local motion vector be provided according to the plurality of regions.

Abstract: Provided is a method of motion estimation for processing a video stream comprising a plurality of frames, the method including segmenting at least one frame, from among the plurality of frames, into a plurality of blocks, determining an event density factor for each block included in a frame, wherein the event density factor of the block corresponds to a number of events accumulated in the block across frames in a predetermined time duration, comparing the determined event density factor with a threshold value, estimating a motion vector of the block based on the comparison, and processing the block in the video stream based on the estimated motion vector of the block.

Abstract: The present disclosure provides a video image decoding method in which a size of an affine motion compensation image sub-block in an affine image block is determined based on a motion vector difference, motion vector precision, a distance between control points in the affine image block, and a size of the affine image block, where the size includes a length in a horizontal direction and a length in a vertical direction, so that a length of the affine image block in a horizontal/vertical direction is an integer multiple of the length of the affine motion compensation image sub-block in the horizontal/vertical direction.

Abstract: Methods and hardware implementations for determining a motion vector between a first frame and a second frame. A block is obtained from the first frame. A reference window is obtained from the second frame. A set of lines are obtained from the block. The set of lines are delayed using a set of delay elements to produce a set of delayed lines. For each location of a search pattern comprising a plurality of locations arranged in a set of rows, a reference window line is obtained from the reference window, a block line is obtained from the set of delayed lines based on which row of the set of rows the location belongs to, and a similarity score of a plurality of similarity scores is accumulated based on the reference window line and the block line. A target location is identified by comparing the plurality of similarity scores.

Abstract: A method of determining a quantization parameter includes determining an adjustment range of a quantization parameter correction value based on a size of a motion area of an input image, calculating an average bitrate value of the input image, and adjusting the quantization parameter correction value by decreasing the quantization parameter correction value within the adjustment range in response to determining that the average bitrate value is greater than an upper limit value, and by increasing the quantization parameter correction value within the adjustment range in response to determining that the average bitrate value is equal to or less than a lower limit value.

Abstract: Detecting objects in video may include receiving object detections for a plurality of selected frames of a video from a still image detector, wherein the plurality of selected frames are non-adjacent frames of the video, propagating the object detections from the plurality of selected frames to sequential frames of the video adjacent to the plurality of selected frames based on a distance metric and vector flow data for the sequential frames, suppressing false positive object detections from the propagating, and outputting resulting object detections for the sequential frames of the video.

Abstract: In a particular implementation, a video decoder may decode an initial motion vector predictor from the bitstream for a current block, and perform motion search in a small search window to refine the initial motion vector predictor. The initial motion vector may be rounded before being refined. The motion refinement can be based on a discontinuity measure between pixels of a current block and pixels of adjacent block, and can also be based on gradients between the current block and adjacent blocks. The motion vector for the current block is then decoded based on the refined motion vector predictor, and the motion vector difference if there is any. The motion refinement can also be performed on the motion vector for the current block directly. Through motion refinement, the decoder may increase the motion resolution. A corresponding video encoder may choose whether to use motion refinement based on encoder decisions.

Abstract: The present disclosure relates to an information processing apparatus, an information processing method and a program as well as a recording medium for enabling at least a bit rate of an image to be reproduced to be converted. A BD-J execution unit sets conversion equation information indicating a conversion equation for converting at least a bit rate of a graphics to be reproduced. A conversion unit converts at least the bit rate of the graphics to be reproduced by use of the conversion equation indicated by the conversion equation information set by the BD-J execution unit. The present disclosure can be applied to a reproducing apparatus and the like for reproducing an optical disc recording therein a stream file of AV stream of main video in a video format different in bit rate or color gamut, a BDJO file, a file of BD-J, and the like.

Abstract: Techniques and tools for video coding/decoding with motion resolution switching and sub-block transform coding/decoding are described. For example, a video encoder adaptively switches the resolution of motion estimation and compensation between quarter-pixel and half-pixel resolutions; a corresponding video decoder adaptively switches the resolution of motion compensation between quarter-pixel and half-pixel resolutions. For sub-block transform sizes, for example, a video encoder adaptively switches between 8×8, 8×4, and 4×8 DCTs when encoding 8×8 prediction residual blocks; a corresponding video decoder switches between 8×8, 8×4, and 4×8 inverse DCTs during decoding.