Abstract: An electronic apparatus is disclosed. The electronic apparatus includes: a memory storing an input image, and a processor configured to: apply a filter to the input image to identify the input image as a plurality of areas, apply a first low-frequency filter to a first area among the plurality of areas, and apply a second low-frequency filter to a second area among the plurality of areas to perform downscaling, wherein a cut-off frequency of the second low-frequency filter is configured to be higher than a cut-off frequency of the first low-frequency filter.

Abstract: A method of method of processing an image of a video sequence including a plurality of images, wherein the video sequence is divided into a sequence of consecutive subsets each including one or more consecutive images of the video sequence is provides, which includes: determining, among the consecutive subsets, a current subset that includes the image, upon determining that the image is a first image of the current subset to be processed, determining an analysis window corresponding to the current subset, wherein the analysis window includes a plurality of consecutive images of the video sequence, and includes at least one image of the current subset, and generating processing results for the image by performing a processing on the images of the analysis window.

Abstract: Methods and systems include receiving, at de-ringing circuitry of a display pipeline of an electronic device, scaled image content based on image data. The de-ringing circuitry also receives a fallback scaler output. The de-ringing circuitry determines whether the image data has a change frequency greater than a threshold. In response to the change frequency being above the threshold, the de-ringing circuitry determines a weight. Based at least in part on the weight, the de-ringing circuitry blends the scaled image content and the fallback scaler output based at least in part on the weight.

Abstract: A video decoding method is disclosed and performed by an electronic device, the method including: obtaining a first resolution used in decoding a current block and a second resolution used in decoding a reference block in a current video frame, the reference block being a reference block used for performing directional prediction on the current block in the current video frame; building a reconstruction block from the reference block; when the first resolution is greater than the second resolution, adjusting the reconstruction block of the reference block to the first resolution to obtain a first reconstruction block; and performing directional prediction on the current block according to the first reconstruction block and the current block.

Abstract: The invention relates to a method for decoding an image based on a base layer (Cbase) and enhancement information (Iam), said method comprising the following steps: decoding said base layer (Cbase) in order to obtain at least one base component (Ydecbase, Udecbase, Vdecbase), oversampling the at least one base component (Ydecbase, Udecbase, Vdecbase) in order to obtain at least one oversampled component (Ysurech, Usurech, Vsurech), decoding the enhancement information (Iam) by means of a part (B) at least of artificial neural network in order to obtain enhancement values (Vam), reconstructing the image based on the at least one oversampled component (Ysurech, Usurech, Vsurech) and the enhancement values (Vam). The invention also relates to associated encoding method, electronic decoding device, electronic encoding device and signal.

Abstract: Embodiments relate to a multi-mode demosaicing circuit able to receive and demosaic image data in a different raw image formats, such as Bayer raw image format and Quad Bayer raw image format. The multi-mode demosaicing circuit comprises different circuitry for demosaicing different image formats that access a shared working memory. In addition, the multi-mode demosaicing circuit shares memory with a post-processing and scaling circuit configured to perform subsequent post-processing and/or scaling of the demosaiced image data, in which the operations of the post-processing and scaling circuit are modified based on the original raw image format of the demosaiced image data to use different amounts of the shared memory, to compensate for additional memory utilized by the multi-mode demosaicing circuit when demosaicing certain types of image data.

Abstract: A method for video processing using Cross-Component Adaptive Loop Filter (CCALF) is provided. The method includes filtering decoded video content using a CCALF, wherein the CCALF is a 24-tap 9×9 filter.

Abstract: The present disclosure provides systems and methods for processing video content using motion compensation interpolation. The methods include: in response to a target picture and a reference picture having different resolutions, applying a band-pass filter to the reference picture, to perform a motion compensated interpolation with reference down-sampling to generate a reference block; and encoding or decoding a block of the target picture using the reference block.

Abstract: Provided are a Reduced Instruction Set Computer-Five (RISC-V)-based artificial intelligence inference method and system. The RISC-V-based artificial intelligence inference method includes the following steps: acquiring an instruction and data of artificial intelligence inference by means of a Direct Memory Access (DMA) interface, and writing the instruction and the data into a memory; acquiring the instruction from the memory and translating the instruction, and loading the data from the memory to a corresponding register on the basis of the instruction; in response to the instruction being a vector instruction, processing, by a convolution control unit, corresponding vector data in a vector processing unit on the basis of the vector instruction; and feeding back the processed vector data to complete inference.

Abstract: Provided are methods and apparatus for creating super-compressed map files. Using free and open-source software (FOSS), the tool create a super-compressed internally tiled Geo Tag Image File Format (TIFF) in a WGS84 datum (WGS84) similar in size to the original LizardTech's MrSID (SID) imagery from the National Geospatial-Intelligence Agency (NGA). Converting NGA data to WGS84 allows mapping systems like NASA Worldwind (WW) to eliminate the step of re-projecting on the fly from non-native projections, thus reducing processing time. The disclosed method includes removing all pure-black pixels by setting them to black+1, changing all near-black border pixels with values less than 15 to 0 (pure black), setting pure black values to “no-data,” compressing the image with a compression scheme, and translating the compressed image to JPEG and a YCbCr color space to achieve greater compression.

Abstract: A deblocking method, for deblocking a transform block boundary within a coding block in an image encoding and/or an image decoding is provided, wherein the coding block comprising transform blocks is coded in inter prediction mode and the transform blocks comprises a first transform block and a second transform block; wherein the method comprises: determining, when the boundary between the first transform block and the second transform block is a transform block boundary and at least one of the first transform block and the second transform block has one or more non-zero transform coefficients, a value of a BS parameter for the boundary between the first transform block and the second transform block to be a first value; and performing de-blocking filtering process to the boundary between the first transform block and the second transform block at least based on the value of the boundary strength parameter.

Abstract: Provided are an encoder, a decoder and methods for applying and varying a strength of a deblocking or deringing filter for filtering a block of a picture, wherein the deblocking filter is configured to determine, for each of at least eight border portions of a border of the block, a dissimilarity between an unfiltered content of the block and a surrounding picture content around the block along the respective border portion, the eight border portions including four corner border portions, each arranged at a corner of the block, and four edge border portions, each arranged at intermediary portions of the border between the corners of the block. Furthermore, the deblocking filter is configured to parametrize a deblocking filtering of the block using the dissimilarities determined for the at least eight border portions in order to obtain a filtered content of the block.

Abstract: When removing a block distortion occurring in a local decoded image, a loop filtering part 11 of an image coding device carries out a filtering process on each of signal components (a luminance signal component and color difference signal components) after setting the intensity of a filter for removing the block distortion for each of the signal components according to a coding mode (an intra coding mode or an inter coding mode) selected by a coding controlling part 1.

Abstract: The present technology relates to a camera, a control method, and a program capable of improving image quality. An image sensor captures an image, and an encoding unit encodes the image. A control unit controls a bit rate to be allocated to encode the image in response to a shake of the camera. The present technology is applicable to, for example, a camera that captures and encodes an image.

Abstract: The disclosure relates to an artificial intelligence (AI) system that uses a machine learning algorithm and an application thereof. A method for controlling an electronic apparatus according to the disclosure includes receiving image data and information associated with a filter set that is applied to an artificial intelligence model for upscaling the image data from an external server; decoding the image data; upscaling the decoded image data using a first artificial intelligence model that is obtained based on the information associated with the filter set; and providing the upscaled image data for output.

Abstract: Systems and methods are provided herein that implement and utilize temporal state machines and other temporal computational/memory circuits. For example, a temporal state machine is provided that comprises a temporal computational unit comprising at least one circuit to perform a time-domain operation, and a temporal memory unit. Both the temporal computational unit and temporal memory unit can operate using solely, or partially, time-encoded wavefronts. The computation unit accesses time-encoded wavefronts from the memory and can output and write time-encoded wavefronts back to the memory.

Abstract: In encoding a picture, comprising a plurality of tiles, into a bitstream, a method and apparatus is provided for signaling the tile attribute values per-tile, using a compact syntax. These embodiments signal per-tile attribute values. The tile attributes may, for example, be in the form of a set of tile syntax elements (one syntax element per tile attribute), or for example in the form of a set of flags to enable or disable the usage of the tile attributes. These embodiments provide freedom for an encoder to assign the tile attribute values per tile, or per any subset of tiles in a picture, and the attribute values are signaled in a compact syntax at least once. A corresponding method and apparatus for decoding a picture is also described.

Abstract: A video picture encoding and decoding method, including obtaining a primary sub-region bitstream corresponding to a target sub-picture of a panoramic picture, where the primary sub-region bitstream includes N secondary sub-region bitstreams, and N is a positive integer, parsing the primary sub-region bitstream to obtain a reconstructed picture, performing cross-sub-region-boundary out-loop filtering on the reconstructed picture when an out-loop filtering identifier instructs to perform cross-sub-region-boundary out-loop filtering on the reconstructed picture, to obtain a filtered reconstructed picture, and adjusting a location of at least one of N sub-regions in the filtered reconstructed picture to obtain a picture having no sub-region boundary.

Abstract: A mechanism is described for facilitating depth and motion estimation in machine learning environments, according to one embodiment. A method of embodiments, as described herein, includes receiving a frame associated with a scene captured by one or more cameras of a computing device; processing the frame using a deep recurrent neural network architecture, wherein processing includes simultaneously predicating values associated with multiple loss functions corresponding to the frame; and estimating depth and motion based the predicted values.

Abstract: A machine learning based image processing architecture and associated applications are disclosed herein. In some embodiments, a machine learning framework is trained to learn low level image attributes such as object/scene types, geometries, placements, materials and textures, camera characteristics, lighting characteristics, contrast, noise statistics, etc. Thereafter, the machine learning framework may be employed to detect such attributes in other images and process the images at the attribute level.

Abstract: Aspects of the disclosure provide methods and apparatuses for video encoding/decoding. In some examples, an apparatus for video decoding includes processing circuitry. The processing circuitry determines offset values associated with a first filter shape configuration of a video filter based on signals in a coded video bitstream that carries a video. The video filter is based on non linear mapping. The number of filter taps of the first filter shape configuration is smaller than five. The processing circuitry applies the video filter on a sample to be filtered, using the offset values associated with the first filter shape configuration.

Abstract: The present disclosure relates to image processing apparatus and method that can suppress the increase in the load of processing multi-wavelength data. A subject is imaged to generate multi-wavelength data that is image data including four or more wavelength components, the generated multi-wavelength data is encoded to generate encoded data of the multi-wavelength data, and the generated encoded data is transmitted. The present disclosure can be applied to, for example, an image processing apparatus, an image encoding apparatus, an image decoding apparatus, an imaging element, an imaging apparatus, or the like.

Abstract: An example device includes a memory and processing circuitry in communication with the memory. The processing circuitry of a device is configured to form a most probable mode (MPM) candidate list for a chroma block of the video data stored to the memory, such that the MPM candidate list includes one or more derived modes (DMs) associated with a luma block of the video data associated with the chroma block, and a plurality of luma prediction modes that can be used for coding luminance components of the video data. The processing circuitry is further configured to select a mode from the MPM candidate list, and to code the chroma block according to the mode selected from the MPM candidate list.

Abstract: Candidate encodes of a source video are produced using a plurality of encoding configurations. Quality of experience (QoE) scores for each of the candidate encodes are computed. The QoE scores of the plurality of candidate encodes are compared to determine a lowest bitrate encode that achieve a target QoE score. The lowest bitrate encode that achieve the target QoE score as an optimized output video is selected.

Abstract: Methods (1100, 1300) and apparatuses (600, 1200) for video coding and decoding are provided. The method of video encoding includes accessing (1110) a reconstructed block corresponding to a block in a picture of a video, determining (1120) at least one filter pattern based on a property of the block and filtering (1130) the reconstructed block according to the at least one filter pattern. The method of video decoding includes accessing (1310) a reconstructed block corresponding to a block in a picture of an encoded video, determining (1320) at least one filter pattern based on a property of the block and filtering (1330) the reconstructed block according to the at least one filter pattern. A bitstream formatted to include encoded data, a computer-readable storage medium and a computer program product are also described.

Abstract: An example method of video processing includes determining, for a conversion between a current video unit of a video and a bitstream representation of the video, availability of one or more samples in a first neighboring region of the current block for a coding process of the conversion independently from information of a second neighboring region of the current block. The second neighboring region is adjacent to the first neighboring region, and the one or more samples are padded in case determined to be unavailable. The method includes performing the conversion based on the determining.

Abstract: A macro block size determining unit 1 determines the size of each macro block on a frame-by-frame basis. A macro block dividing unit 2 divides an inputted image into macro blocks each having the size determined by the macro block size determining unit 1. A macro block coding unit 3 determines a coding mode for each of the macro blocks divided by the macro block dividing unit 2, and codes pixel values in each of the macro blocks in the determined coding mode.

Abstract: Compensation offsets are provided for a set of reconstructed samples of an image. Each sample has a sample value. A method of providing the compensation offsets comprises selecting, based on a rate distortion criterion, a classification from among a plurality of predetermined classifications. Each predetermined classification has a classification range smaller than a full range of the sample values and is made up of a plurality of classes, each defining a range of sample values within the classification range, into which class a sample is put if its sample value is within the range of the class concerned. A compensation offset is associated with each class of the selected classification for application to the sample value of each sample of the class.

Abstract: A method and apparatus of video coding incorporating Deep Neural Network are disclosed. A target signal is processed using DNN (Deep Neural Network), where the target signal provided to DNN input corresponds to the reconstructed residual, output from the prediction process, the reconstruction process, one or more filtering processes, or a combination of them. The output data from DNN output is provided for the encoding process or the decoding process. The DNN can be used to restore pixel values of the target signal or to predict a sign of one or more residual pixels between the target signal and an original signal. An absolute value of one or more residual pixels can be signalled in the video bitstream and used with the sign to reduce residual error of the target signal.

Abstract: A display device includes a display unit including gate lines and pixels electrically coupled to the gate lines; a timing controller configured to generate an on-clock signal, an off-clock signal, an enable signal, and a common signal; a clock generator configured to generate a plurality of clock signals having different phases based on the on-clock signal and the off-clock signal, when the enable signal has a first voltage level, wherein the clock generator is to insert a common pulse into each of the plurality of clock signals based on the common signal, when the enable signal has a second voltage level different from the first voltage level; and a gate driver configured to generate gate signals based on the plurality of clock signals, and to sequentially provide the gate signals to the gate lines.

Abstract: Aspects of the disclosure provide methods and apparatuses for video encoding/decoding. In some examples, an apparatus for video decoding includes processing circuitry. The processing circuitry reconstructs a first sample in a video carried in a coded video bitstream based on a non linear mapping based filter with a first filter shape configuration. Then, the processing circuitry determines a switch from the first filter shape configuration to a second filter shape configuration, and reconstructs a second sample in the video based on the non linear mapping based filter with the second filter shape configuration.

Abstract: Approaches to robust encoding and decoding of escape-coded pixels in a palette mode are described. For example, sample values of escape-coded pixels in palette mode are encoded/decoded using a binarization process that depends on a constant value of quantization parameter (“QP”) for the sample values. Or, as another example, sample values of escape-coded pixels in palette mode are encoded/decoded using a binarization process that depends on sample depth for the sample values. Or, as still another example, sample values of escape-coded pixels in palette mode are encoded/decoding using a binarization process that depends on some other fixed rule. In example implementations, these approaches avoid dependencies on unit-level QP values when parsing the sample values of escape-coded pixels, which can make encoding/decoding more robust to data loss.

Abstract: An image encoding/decoding method and apparatus are provided. An image decoding method performed by an image decoding apparatus may comprise deriving a reconstructed block for a current block, deriving a target boundary for the reconstructed block, determining a filter length of a deblocking filter to be applied for the target boundary, and applying the deblocking filter for the target boundary based on the determined filter length. The filter length may be determined based on at least one of a width or height of a transform block adjacent to the target boundary.

Abstract: In encoding a picture, comprising a plurality of tiles, into a bit-stream, a method and apparatus is provided for signaling the tile attribute values per-tile, using a compact syntax. These embodiments signal per-tile attribute values using a loop over the tiles. The tile attributes may, for example, be in the form of a set of tile syntax elements (one syntax element per tile attribute), or for example in the form of a set of flags to enable or disable the usage of the tile attributes. These embodiments provide freedom for an encoder to assign the tile attribute values per tile, or per any subset of tiles in a picture, and the attribute values are signaled in a compact syntax using a loop (or loops) over tiles.

Abstract: Techniques for encoding and decoding media content, and more specifically to selecting filter coefficients for filtering coding artifacts from the encoded media content are described. The filter coefficients are selected by an encoder for a given frame based on a statistical record of one or more previous frames in a data stream. The statistical record indicates the effectiveness of different sets of filter coefficients in reducing encoding artifacts for the one or more previous frames. By employing the statistical record to select filter coefficients for the next frame in the data stream, the encoder is able to select the filter coefficients relatively quickly, reducing encoding latency while ensuring that a decoder is able to effectively decode the encoded frames.

Abstract: Provided is a video decoding method of applying a deblocking filter to neighboring pixels adjacent to a boundary of a current block, the video decoding method including selecting a deblocking filter to be applied to the neighboring pixels from among a plurality of deblocking filters according to pixel values of the neighboring pixels and a size of the current block, and applying the selected deblocking filter to the neighboring pixels, wherein the plurality of deblocking filters include three or more deblocking filters having different ranges of neighboring pixels to which deblocking filtering is applied.

Abstract: A method for image processing is provided. The method may include: obtaining a plurality of frames, each of the plurality of frames comprising a plurality of pixels; determining, based on the plurality of frames, whether a current frame of the plurality of frames comprises a moving object; in response to determining that the current frame includes no moving object, obtaining a first count of frames, and generating a target image by superimposing the first count of frames; in response to determining that the current frame includes a moving object, obtaining a second count of frames, and generating the target image by superimposing the second count of frames.

Abstract: A process for determining the selection of filters and input samples is provided for scalable video coding. The process provides for re-sampling using video data obtained from an encoder or decoder process of a base layer (BL) in a multi-layer system to improve quality in Scalable High Efficiency Video Coding (SHVC). It is proposed that a single scaled reference layer offset be derived from two scaled reference layer offset parameters, and vice-versa. It is also proposed that a single scaled reference layer offset or a single reference layer offset be derived from a combination of a scaled reference layer offset parameter and a reference layer offset parameter.

Abstract: An autostereoscopic image output device includes an image panel having an array of image pixels defining an image, the image pixels being arranged in rows and columns. An array of parallel lenticular elements is positioned over the image panel, the lenticular elements having optical focal axes that are slanted at an angle (?) to the image pixel columns. The image output device is operable in first and second modes, with the image panel and lenticular element array rotated by 90 degrees between the modes, thereby providing a landscape mode of operation and a portrait mode of operation, the slant angle ? in the landscape mode satisfies 1???½.