Abstract: Provided are a color adjustment method, a color adjustment device, an electronic device, and a computer-readable storage medium. The method includes: determining an adjustment area corresponding to an edge pixel, where the adjustment area includes multiple pixels; acquiring color information of the edge pixel and color information of each similar pixel in the adjustment area, where a pixel type of the similar pixel is consistent with a pixel type of the edge pixel; and adjusting a parameter value of the edge pixel according to the color information of the each similar pixel, the color information of the edge pixel, and a brightness parameter of the edge pixel.

Abstract: A method for determining information on an expected trajectory of an object comprises: determining input data being related to the expected trajectory of the object; determining first intermediate data based on the input data using a machine-learning method; determining second intermediate data based on the input data using a model-based method; and determining the information on the expected trajectory of the object based on the first intermediate data and based on the second intermediate data.

Abstract: An object detection method, for detecting a target object, comprising: capturing at least two detection portions with a first aspect ratio from an input image with a second aspect ratio; confirming whether any object is detected in each of the detection portions and obtaining corresponding boundary boxes for detected objects; and wherein the first aspect ratio is different to the second aspect ratio.

Abstract: This application relates to a method and a system for compressing a captured image of an item such as a mailpiece or parcel. The system may include a memory configured to store images of a plurality of items captured while the items are being transported and a processor in data communication with the memory. The processor may be configured to receive or retrieve one or more of the captured images, perform a wavelet scattering transform on the one or more captured images, perform deep learning on the wavelet scattering transformed images to classify the wavelet scattering transformed images and compress the classified wavelet scattering transformed images. Various embodiments can significantly improve a compression efficiency, a communication efficiency of compressed data and save a memory space so that the functionality of computing devices is significantly improved.

Abstract: Embodiments relate to an image processing circuit able to perform image fusion on received images in at least a first mode for fusing demosaiced and downscaled image data, and a second mode for fusing raw image data. Raw image data is received from an image sensor in Bayer RGB format. In the first mode, the raw image data is demosaiced and resampled prior to undergoing image fusion. On the other hand, in the second raw image mode, the image processing circuit performs image fusion on the raw Bayer image data, and demosaics and resamples the generated fused raw Bayer image. This may ensure a cleaner image signal for image fusion, but consumes more memory. The image processing circuit is configured to support both modes of operation, allowing for fused images to be generated to satisfy the requirements of different applications.

Abstract: Disclosed is a rendering system that dynamically changes the resolution at which image data in a field-of-view (“FOV”) is rendered based on the proximity or depth of the image data relative to the render position or camera position. The rendering system selects the image data that is within the FOV, and generates a depth map with a set of distance measures for different distances or depths of the image data in the FOV. The rendering system selects a dynamic resolution at which to render the FOV based on the set of distance measures from the depth map, and renders the image data and/or FOV at the dynamic resolution.

Abstract: Systems and methods for down-scaling are provided. In one example, a method for processing image data includes determining a plurality of output pixel locations using a position value stored by a position register, using the current position value to select a center input pixel from the image data and selecting an index value, selecting a set of input pixels adjacent to the center input pixel, selecting a set of filtering coefficients from a filter coefficient lookup table using the index value, filtering the set of source input pixels to apply a respective one of the set of filtering coefficients to each of the set of source input pixels to determine an output value for the current output pixel at the current position value, and correcting chromatic aberrations in the set of source input pixels.

Abstract: Systems and methods for suppressing off-axis sidelobes and/or clutter, near-field reverberation clutter, and/or grating lobe contributions are disclosed. A dual apodization with median (DAM) filtering technique is disclosed. The dual apodization technique may include summing aligned channel data with apodization functions (406, 412, 414) with complementary apertures applied. Median values for a zero function (RF3) and the resulting signals (RF1, RF2) from the complementary apertures are determined to generate a median value signal (416, MVS). The median value signal is used to generate an ultrasound image with enhanced image contrast. A method of image smoothing of the ultrasound image with enhanced image contrast is also disclosed. The smoothed image may include low frequency components of the ultrasound image with enhanced image contrast and high frequency components of an original image.

Abstract: There is provided an image signal processing apparatus, comprising a demosaic processing unit receiving input of mosaic image data of each of signals obtained by a single plate imaging device having an element array composed of visible light obtaining elements obtaining visible light signals, and invisible light obtaining elements obtaining signals including invisible light components, and generating a demosaic image of each of the obtained signals; and a noise reduction processing unit receiving input of the demosaic image to execute correction of pixel values of the demosaic image obtained by the visible light obtaining elements on the basis of edge information extracted from the demosaic image of the signals obtained by the invisible light obtaining elements.

Abstract: An image processing method and an image processing apparatus for removing noise from an image are disclosed. A provided image processing method includes: dividing an input image into a luminance signal and a chrominance signal; removing noise from the luminance signal; restoring luminance signal present in the noise removed from the luminance signal; removing noise from the chrominance signal; and combining the luminance signal and the chrominance signal from which the noises are removed. Accordingly, an image of which an edge component is well preserved and a degree of color noise is low is generated not only in a general environment but also in a low light level and high sensitivity environment having a large amount of noise.

Abstract: An image may be processed to normalize and/or remove noise from the image. The processing of the image may involve decomposition of the image into multiple components and subsequent gray scale registration across multiple scales.

Abstract: A method includes implementing, through a processor communicatively coupled to a memory and/or a hardware block, a Bilateral Filter (BF) including a spatial filter component and a range filter component, and implementing the spatial filter component with a low-complexity function to allow for focus on the range filter component. The method also includes determining, through the processor, filter tap value(s) related to the range filter component as a function of radiometric distance between a pixel of a video frame and/or an image and other pixels thereof based on a pre-computed corpus of data related to execution of an application in accordance with a filtering requirement of the pixel by the application. Further, the method includes constraining, through the processor, the filter tap value(s) to a form i×base based on the BF implementation. i is an integer and base is a floating point base.

Abstract: A program is implemented on a processor for executing the following steps: receiving images of a scene comprising successive frames from a camera, each frame including an array of pixels; filtering intensities of the array of pixels in a respective frame by using a Bessel Filter to compute a constant value for the respective frame; and summing a predetermined number of respective frames from the camera to determine rapid motion in the scene. The filter includes a Bessel filter, which is an n-pole recursive digital filter, where n is a positive integer.

Abstract: Methods and composition for denoising digital camera images are provided herein. The method is based on directly measuring the local statistical structure of natural images in a large training set that has been corrupted with noise mimicking digital camera noise. The measured statistics are conditional means of the ground truth pixel value given a local context of input pixels. Each conditional mean is the Bayes optimal (minimum mean squared error) estimate given the specific local context. The conditional means are measured and applied recursively (e.g., the second conditional mean is measured after denoising with the first conditional mean). Each local context vector consists of only three variables, and hence the conditional means can be measured directly without prior assumptions about the underlying probability distributions, and they can be stored in fixed lookup tables.

Abstract: A method and an apparatus are provided for eliminating noise in a digital image. An ambient image and at least one flash image are captured in succession of a given location. At least one image alignment technique is applied for the ambient image and the at least one flash image. Joint mean shift filtering is applied to the at least one flash image to obtain filter weights. The filter weights are applied to the ambient image to eliminate noise in the ambient image.

Abstract: In accordance with an embodiment of the invention, an anisotropic denoising method is provided that removes sensor noise from a digital image while retaining edges, lines, and details in the image. In one embodiment, the method removes noise from a pixel of interest based on the detected type of image environment in which the pixel is situated. If the pixel is situated in an edge/line image environment, then denoising of the pixel is increased such that relatively stronger denoising of the pixel occurs along the edge or line feature. If the pixel is situated in a detail image environment, then denoising of the pixel is decreased such that relatively less denoising of the pixel occurs so as to preserve the details in the image. In one embodiment, detection of the type of image environment is accomplished by performing simple arithmetic operations using only pixels in a 9 pixel by 9 pixel matrix of pixels in which the pixel of interest is situated.

Abstract: A system and method for generating a fused image is provided. The system comprises processing circuitry configured to receive a plurality of images, filter each received image using an edge preserving filter, compute a weight for each received image based on the corresponding filtered image and the received image and generate a fused image based on the weights of each received image. The system further comprises a memory device configured to store the fused image.

Abstract: Systems are provided for determining toner color having a processor that generates a fluorescent toner color image that when printed using a corresponding fluorescent toner will generate a diffuse fluorescent color light that reduces the extent to which noise induced variations in density in a noise evident portion of a toner print are observable. The processor further adjusts reflective toner color images used to form the toner print so that the reflective toner color images combine with the fluorescent color image to form a target color image.

Abstract: An image processing apparatus includes a data storing portion configured to store coefficient data for reconstructing an optical transfer function of an image pickup optical system in accordance with a type of the image pickup optical system and an imaging condition, a tap number determining portion configured to determine a tap number of the optical transfer function that is reconstructed by using the coefficient data in accordance with a size of one pixel of an image pickup element, and a reconstruction portion configured to reconstruct the optical transfer function in accordance with Nyquist frequency of the image pickup element and the tap number in a frequency space.

Abstract: An apparatus of reducing noise includes: an edge determining module determining whether each pixel of an image corresponds to an edge; a low pass filter module performing low pass filtering of the image in two directions and performing low pass filtering only for the pixel determined not to be the edge; a filter selecting module selecting a filter having a flexible size to be applied to a mask region for each of the images low pass filtered based on the average brightness of the entire region and the average brightness of the mask region having a predetermined size; a sigma filter module sigma filtering the mask region using the selected filter for each of the images low pass filtered; and an averaging module averaging the image sigma filtered in the two directions.

Abstract: A set of pixels of a background element is identified according to a mask that defines a shape of a foreground element. A color value for a pixel of the foreground element is determined. The determining includes ascertaining a value of a measure of brightness of one or more pixels of a set of pixels of the background element and calculating the color value for the pixel of the foreground element based on the value of the measure of brightness and a value of an adjustable contrast variable. The calculating the color value for the pixel of the foreground element preserves in the foreground element a color component of the one or more pixels of the set of pixels of the background element and increases contrast with the value of the measure of brightness according to the value of the adjustable contrast variable.

Abstract: It is an object to provide an image processing device capable of obtaining a high precise image while aberration asymmetry is corrected. An image processing device according to the present invention includes image obtaining means configured to obtain an input image, image restoration means configured to restore the input image using a generated or selected image restoration filter in accordance with a transfer function of an image pickup system used for forming the input image from an object image. The image restoration filter makes a difference between absolute values of transfer functions of two azimuthal directions at a time when the restoration image is obtained from an object smaller than a difference between absolute values of transfer functions of the two azimuthal directions of the image pickup system.

Abstract: Analysis filter processing is recursively repeated on horizontal and vertical low frequency component coefficients obtained as a result of the analysis filter processing, until a predetermined decomposition level is reached. Coefficients obtained during a process of computation in the analysis filter processing and, except for a preset decomposition level, horizontal and vertical low frequency component coefficients obtained as a result of the computation in the analysis filter processing are stored in a first storage section independently for each decomposition level. The coefficients stored in the first storage section are read as appropriate and the read coefficients are supplied for the analysis filter processing. The horizontal and vertical low frequency component coefficients of the preset decomposition level are stored in a second storage section. The coefficients stored in the second storage section are read as appropriate. The read coefficients are supplied for the analysis filter processing.

Abstract: An information processing apparatus comprises: a spatial filtering unit configured to perform spatial filtering in a frequency range based on a spatial frequency of an object for image data of a current frame; and a recursive filtering unit configured to perform recursive filtering by obtaining image data, which has been processed prior to the current frame, from a memory, multiplying the obtained image data by a coefficient ? (?<1), adding the image data multiplied by the coefficient ? to the image data of the current frame after the spatial filtering, and storing the image data after the addition in the memory.

Abstract: A method according to the invention enhances contrast of an image by accessing an original image, and establishing, assigning, or initializing pixel values and pixel coordinates of pixels of the image. Then, a Laplacian pyramid having an integral number of levels is generated for the image. A contrast boost pyramid is generated and applied to the Laplacian pyramid to obtain a modified Laplacian pyramid wherein values in the levels of the Laplacian pyramid are enhanced. An enhanced image is then constructed from the modified Laplacian pyramid.

Abstract: An acquired signal indicative of electrophysiological activity is filtered using both a wavelet filter and either a notch filter or a band-pass filter to eliminate noise or interference, such as power line interference. A wavelet transform is used to transform the acquired signal into the wavelet domain, where a wavelet filter is applied to extract a soft component (e.g., a component with small wavelet coefficients). A filter, such as a notch filter or a band-pass filter, is applied to the soft component in order to isolate an interference signal. The interference signal is used to produce an output signal representing the acquired signal filtered to eliminate the interference signal. For example, the interference signal may be subtracted from the acquired signal. Alternatively, the output signal may be reconstructed from respective hard and soft components of the acquired signal as transformed into the wavelet domain.

Abstract: One embodiment of the present invention provides a system for applying a bilateral filter to an image. During operation, the system selects a first region within the image which is associated with a first pixel. Next, the system constructs a first histogram using pixel values within the first region. The system then computes a new value for the first pixel using the current value of the first pixel and the first histogram. The system then selects a second region within the image which is associated with a second pixel. Next, the system determines a non-overlapping region between the first region and the second region. The system then constructs a second histogram using the first histogram and pixel values in the non-overlapping region. Next, the system computes a new value for the second pixel using the current value of the second pixel and the second histogram.

Abstract: A system for processing video data to improve image quality at low data rates comprising an encoder generating an entropy signal representing the relative entropy of the video data and a plurality of filters each receiving the entropy signal and a threshold setting and filtering the video data if the entropy signal is greater than the threshold setting.

Abstract: Provided are an image processing method and apparatus for effectively reducing noise in an image, and a recording medium storing a program for executing the method. The image processing apparatus includes a noise reduction unit configured to apply a noise reduction filter to first image data to obtain second image data; a first edge data obtaining unit configured to calculate edge data lost in the second image data compared with the first image data to obtain the first edge data; and a first synthesis unit configured to tune the first edge data and calculate third image data from the second image data and the tuned first edge data.

Abstract: A system is provided for processing video images for display. In one example, the system comprises a stream parser for retrieving a compressed main video data and a sub-picture identifier. A video decoder generates a main video image having a main video intensity value for each pixel in the main video. A sub-picture decoder determines a sub-picture image based on the sub-picture identifier. The sub-picture image includes a pixel data for each pixel in the sub-picture image indicative of a sub-picture pixel type including a background pixel type and a pattern pixel type. Each pixel includes a command code indicative of a background contrast level, a pattern contrast level, a background color level and a pattern color level. An intensity formatter generates a sub-picture pixel intensity for each pixel in the sub-picture image.

Abstract: A method for detecting a temporally oscillating source in digital video signals includes: using an imaging device to capture a sequence of input images of a scene; generating digital video signals from the sequence of input images; and processing the digital video signals using a recursive Infinite Impulse Response (IIR) filter technique based on a differentiated version of Goertzel's Algorithm to detect a temporally oscillating source in the digital video signals. In various embodiments, the method also includes generating a visual display of the scene including one or more graphical elements at least one of which pertains to a detected temporally oscillating source.

Abstract: Disclosed herein are a method, system, and computer program product for aligning an input video frame from a video sequence with a background model associated with said video sequence. The background model includes a plurality of model blocks (820, 830), each one of the plurality of model blocks (820, 830) being associated with at least one mode (821, 822, 823, 831, 832, 833, 834), wherein each mode (821, 822, 823, 831, 832, 833, 834) includes a plurality of frequency domain attributes. The method selects, for each one of the plurality of model blocks, a reference mode dependent upon a mode of the corresponding model block, generates a background reference image (840) comprising the plurality of selected reference blocks (841, 842), and then aligns the input frame with the background model (810), based on the background reference image (810).

Abstract: An image processing device capable of obtaining a high precision image while aberration asymmetry is corrected. An image processing device includes image obtaining means configured to obtain an input image, image restoration means configured to restore the input image using a generated or selected image restoration filter in accordance with a transfer function of an image pickup system used for forming the input image from an object image. The image restoration filter makes a difference between absolute values of transfer functions of two azimuthal directions at a time when the restoration image is obtained from an object smaller than a difference between absolute values of transfer functions of the two azimuthal directions of the image pickup system.

Abstract: A method is provided in one example embodiment that includes receiving a plurality of depth values corresponding to pixels of an image; and filtering the image as a function of a plurality of variations in the depth values between adjacent pixels of a window associated with the image. In more detailed embodiments, the method may include encoding the image into a bit stream for transmission over a network. The filtering can account for a bit rate associated with the encoding of the image.

Abstract: A region-based method for iterative regularization image enhancement, includes: for each region of a plurality of regions of an image, performing at least one gradient calculation of an objective function of a latest representative function of the region and updating the latest representative function according to the gradient calculation; and for the region of the plurality of regions of the image, when at least one predetermined convergence criterion is not satisfied, iteratively updating the latest representative function according to at least one gradient calculation of the same objective function of the latest representative function. In particular, the region-based method further includes: for the region of the plurality of regions of the image, when the predetermined convergence criterion is satisfied, performing postprocessing on the latest representative function of the region to generate an iteratively regularized partial image corresponding to the region.

Abstract: A histogram modeling based technique for image contrast enhancement. In some implementations, a histogram of an image is created and then transformed. Using the physics of sound or heat propagation, the technique may develop a spreaded histogram model that may be transformed. A nonlinear mapping may be created to remap an image for contrast enhancement. The technique may be performed without threshold tuning and may be implemented on a variety of display hardware.

Abstract: Unnecessary flare correction at the boundary between a blanking area and video signal area is suppressed. An image quality improving apparatus includes 2-dimensional low-pass filter circuit 2 that extracts low-frequency components from an input video signal; subtractor circuit 4 that obtains high-frequency components by subtracting the low-frequency components extracted by 2-dimensional low-pass filter circuit 2 from the input video signal; and adder circuit 6 that adds the high-frequency components obtained by subtractor circuit 4 as a correction signal to the input video signal. The input video signal contains blanking signals without any video information. 2-dimensional low-pass filter circuit 2 starts extraction of the low-frequency components after a lapse of a predetermined unit time from when the input video signal changed from the blanking signal to the signal that contains the video information.

Abstract: The invention relates to an iterative method for determining an interpolated video information value in an image that exhibits a number of image regions arrayed for example in matrix fashion, at least one of which is an image region to be interpolated, and that is disposed temporally between a first image and a second image of an image sequence.

Abstract: An image processing apparatus includes a data storing portion configured to store coefficient data for reconstructing an optical transfer function of an image pickup optical system in accordance with a type of the image pickup optical system and an imaging condition, a tap number determining portion configured to determine a tap number of the optical transfer function that is reconstructed by using the coefficient data in accordance with a size of one pixel of an image pickup element, and a reconstruction portion configured to reconstruct the optical transfer function in accordance with Nyquist frequency of the image pickup element and the tap number in a frequency space.

Abstract: The present invention provides an image processing device and an image display system achieving image quality improvement in moving picture by suppressing a motion blur in a hold-type display device, while maintaining low cost. The image processing device processes image data provided from outside and outputting the image data to a hold type display device. The image processing device includes a correction processing section performing a correction process to correct a pixel value in the image data for each pixel through performing a spatial HPF (high pass filter) process on the image data in a frame to be displayed in the display device according to a magnitude of a motion vector in the image data, the HPF process allowing an overshoot region and an undershoot region to be provided in a vicinity of both ends of the changing edge portion in the image data.

Abstract: An information processing apparatus includes: a first generating unit which generates, based on feature points detected on a cepstrum from an input image, a point-spread function that represents the degree of blurring generated in the input image; a second generating unit which generates a structure that represents an image obtained by reducing the input image with a size based on the point-spread function and enlarging this with the size, based on the point-spread function; and an updating unit which executes an updating process to update at least either the point-spread function or the structure such that the point-spread function and the structure approximate to a true value, with the updating unit repeatedly executing the updating process to set, of a structure component and a texture component making up the updated structure, the structure component as a new updated structure, and set the updated point-spread function as a new updated target.

Abstract: An image processing apparatus can perform time-sequential weighting addition processing on a moving image constituted by a plurality of frames includes a filter unit configured to obtain an image by performing recursive filter processing on a frame image that precedes a present target frame, which is one of the plurality of frames constituting the moving image, a coefficient acquisition unit configured to acquire a weighting coefficient for the present target frame based on a noise statistic of a differential image between an image of the present target frame and the image obtained by the filter unit, and an addition unit configured to perform addition processing on the moving image constituted by the plurality of frames based on weighting coefficients acquired by the coefficient acquisition unit.

Abstract: The present invention relates to an apparatus for reducing motion blur in a video signal, comprising an analysing means for determining edge characteristics of an input video signal and for providing motion estimation of an edge within said input video signal, generation means for generating a synthetic detail signal dependent on said edge characteristics and said motion estimation, and an adding means for adding the detail signal to the edge within the input video signal and outputting an output video signal. The present invention further relates to a method for reducing motion blur in a video signal.

Abstract: In a pixel interpolation apparatus for interpolating pixels, an edge pixel detection unit detects edge pixels constituting an edge among pixels on lines positioned above/below the interpolation pixel. A continuous edge detection unit detects edge pixels in which two pixels or more consecutively line up among edge pixels detected by the edge pixel detection unit as a continuous edge. A continuous edge pair detection unit determines the combination of the continuous edges detected on each of the lines above and below the interpolation pixel among the continuous edges detected by the continuous edge detection unit. An edge direction determination unit determines the edge direction of the interpolation pixel on the basis of the positional relation of one set of continuous edges determined by the continuous edge pair detection unit. An interpolation pixel calculation unit calculates an interpolation pixel using the edge direction determined by the edge direction determination unit.

Abstract: A system and method for smoothing digital images using a non-orthogonal convolution kernel involves steps for rearranging and remapping input image data and the convolution kernel image from hexagonal coordinate mapping to orthogonal mapping of a memory space thus enabling implementation of a general box filter convolution strategy to smooth the input image.

Abstract: Signal processing techniques are applied to digital image data to remove the distortion caused by motion of the camera, or the movement of the subject being photographed, or defective optics, or optical distortion from other sources. When the image is captured, the effect of relative motion between the camera and the subject is that it transforms the true image into a blurred image according to a 2-dimensional transfer function. The 2-dimensional transfer function representing the motion is derived using blind estimation techniques or by using information from sensors that detect the motion. The transfer function is inverted and used to define a corrective filter. The filter is applied to the image and the blur due to the motion is removed, restoring the correct image. Another embodiment uses the transfer function to avoid blur by combining multiple consecutive images taken at a fast shutter speed.

Abstract: An apparatus and a method for filtering noise in an image signal are provided. The apparatus includes an analog-to-digital converter (ADC), a first filter, and a second filter. The ADC receives the image signal and converts the image signal into a digital signal. The first filter receives the digital signal and filters a first noise portion of the digital signal to generate a first signal. The second filter coupled to the first filter receives the first signal and filters a second noise portion of the first signal, wherein the first noise portion is a sampled-based impulse noise, and the second noise portion is a line-based impulse noise.

Abstract: A method of pre-processing an image to identify processes for subsequent processing of the image, comprising the steps of: a) investigating portions of the image using a spatial filter; b) calculating for a first plurality of regions within a portion of the image under investigation respective metrics as a function of intensity within those regions; c) selecting combinations of regions within the portion of the image under investigation and processing them to obtain a second plurality of filter values, where the second plurality is greater than the first plurality; and d) comparing the filter values with process thresholds for subsequent processes so as to identify subsequent processes that can be skipped.

Abstract: An upscaler is disclosed that upscales each of a maximum value map, a minimum value map and an average value map to a destination resolution. A blending module generates a detail-enhanced upscaled image of the source image having the destination resolution by blending corresponding pixel values from an upscaled image of the source image with at least one of: the upscaled maximum value map and the upscaled minimum value map. The blending may be based on the strength of detected edges in the source image and further based on a comparison of each pixel value in the upscaled image with a corresponding pixel value in an average value map. A source image characteristic calculator may generate the maximum value map, the minimum value map and the average value map based on the intensity values of a source image.

Abstract: The invention relates to a medical system comprising a detection device for detecting an object in at least two dimensions by x-rays. The detection device is constructed to detect the object and to produce data comprising a 2D data record or a sequence of 2D data records over time representing the object in a projection through the object in two dimensions and to output the data. The medical system comprises at least one storage device with a data input actively connected to the detection device and which is constructed to receive the data at the input side and to write on a storage medium, in particular a portable storage medium, in such a way that the storage medium represents the data so it can be read out again. The medical system is constructed to digitally transmit the data from the detection device through to the storage device.