Abstract: Methods and devices receive color settings into a computerized device. The color settings can identify at least one first color that is indistinguishable from at least one second color by a user. Such methods and devices also receive instructions into the computerized device to output an item has at least one feature having a feature color. Based on the feature color being included within the color settings, these methods and devices automatically alter the item using the computerized device by optionally changing the feature color to a black-based color and automatically adding text to the feature in the altered item using the computerized device. The added text describes the feature color. Also, such methods and devices output the altered item from the computerized device.

Abstract: An image editing device of the present invention replaces part of a first image that has been subjected to lossy compression with a second image, and comprises a image quality adjustment section for carrying out image quality conversion processing that is the same as image quality variation arising due to the lossy compression, and an editing section for carrying out editing processing using the second image that has been adjusted by the image quality adjustment section.

Abstract: An edge graph in which a pixel of an image is set as a node and an edge is set between nodes is generated. The dissimilarity or similarity between nodes at the two ends of the edge is used as the feature amount of the edge, and the edge is classified into one of a plurality of classes based on the feature amount. The edge of interest is selected in ascending class order of the feature amount, and it is determined whether to merge determination target regions to which the nodes at the two ends of the edge of interest belong. Determination target regions determined to be able to be merged are merged, and a feature amount in the merged region is updated.

Abstract: A method for the reduction of noise in an image including identifying neighboring pixel values in pixels proximate to a subject pixel; comparing the neighboring pixel values to a preset tolerance range; using neighboring pixel values within the tolerance range to calculate a pixel intensity correction value; and applying the pixel intensity value to the subject pixel.

Abstract: An embodiment of a method for reducing chroma noise in digital image data and of a corresponding image processor. Chrominance components are subjected to low-pass filtering. The strength of the low-pass filtering is modulated in accordance with the dynamic range of the luminance signal and the dynamic range of each of the two chrominance signals in order to avoid color bleeding at image-object edges. Moreover, the low-pass filtering is selectively applied to pixels with similar luminance and chrominance values only. A combination of down-sampling and up-sampling units is employed so that comparatively small filter kernels may be used for removing chroma noise with low spatial frequency.

Abstract: A method and apparatus for generating an image of a seal impression. N still images of a face of a seal are combined. N is at least 2. The N still images of the face correspond respectively to N beams of light that had previously irradiated the face in succession from N respective different directions respectively corresponding to N different angles of incidence of the light on the face. The combining of the N images include generating in the composite image a common area of pixels that commonly appears on the face of the seal in all still images of the N still images. The common area includes a character area pertaining to where an engraved character is located on the face of the seal.

Abstract: Color image data is compressed by determining the number of colors within a cell of an input image, each cell comprising an N×M array of pixels; in response to determining that the number of colors is greater than a first predetermined threshold, compress the cell using lossy compression; and in response to determining that the number of colors is less than the first predetermined threshold, reduce the number of colors.

Abstract: Methods of filtering random noise and salt and pepper noise that minimize a loss of detail in an image are described. Sample values of an image that are within a tolerance within a sliding window are used to normalize a sample centered in the sliding window to filter random noise and minimize a loss of detail in an image. Sample values of an image in a sliding window are sorted into a sorted array, and mapped to values based on pre-defined regions of the sorted array to filter salt and pepper noise and minimize a loss of detail in an image.

Abstract: Embodiments of the present invention provide an image processing method and device. In the embodiments of the present invention, conversion processing is performed on an input image, which effectively eliminates an impact on image quality from such weather conditions as fog, dust-haze, sand storm and rain where atmospheric transparency is low, and can solve a problem in the prior art that image quality of a captured image or video is poor due to a scattering function of suspended particles in the atmosphere under such weather conditions as fog, dust-haze, sand storm and rain where atmospheric transparency is low, thereby improving contrast, saturation, and sharpness of an image or a video (namely, a multi-frame image). The technical solutions according to the present invention are easy to be implemented and have a low cost.

Abstract: Color correction of an image is implemented with a small circuit scale. A color correction section performs a color correction process on a pixel group-by-pixel group basis, and each pixel group is comprised of a plurality of adjoining pixels. A representative point generation section generates, e.g., a green (G) image signal of a representative point located as an imaginary point in the pixel group. A subtraction section subtracts the G-image signal of the representative point from an image signal of a G-pixel in the pixel group. A representative point color correction section performs the color correction process on the G-image signal of the representative point. An addition section adds the color-corrected G-image signal of the representative point to the output of the subtraction section.

Abstract: In a system and method of reducing noise, an image sensor with a color filter array (CFA) outputs raw data, and a noise reduction device corrects the raw data according to distances between an original current pixel and neighboring same-color pixels in a process mask, thereby generating a new current pixel so as to output corrected raw data. A color interpolation device couples to receive the corrected raw data to result in full-color data.

Abstract: A method of converting a video file to a Graphics Interchange Format (GIF) image includes converting a plurality of frames of a video file into corresponding frames of a GIF image, creating a first palette table for defining colors in each frame of a first set of consecutive frames of the GIF image, and creating a second palette table for defining colors in each frame of a second set of consecutive frames of the GIF image, wherein the first palette table is not equal to the second palette table and each frame in the first set of consecutive frames is distinct from each frame in the second set of consecutive frames.

Abstract: An image processing apparatus includes a buffer unit which stores image data of one input image, an input control unit which causes the buffer unit to store the image data of the input image, a processing operation unit which outputs image data of a processed image generated by performing image processing based on one of a plurality of set processing conditions, a plurality of output control units corresponding to the processing conditions, wherein each output control unit causes the image data necessary when image processing is performed in a corresponding processing condition to be output from the buffer unit to the processing operation unit and causes the image data of the processed image to be output to a subsequent-stage processing circuit, and an output arbitrating unit which determines which processing condition is used to perform the image processing and permits the corresponding output control unit to perform output control.

Abstract: Methods and systems for super resolution encoding. A matching pattern can be encoded with respect to an original pattern to generate a matching function for converting a screen into an IOT screen. Then, an operation can be implemented for accounting for a disturbance that causes a change in gray value that includes a minimal error while remaining close to the original pattern. The gray value is then mapped to the matching pattern via the matching function to convert the screen into the IOT screen and thereby minimize the effects of lossy compression and data variations caused by the disturbance.

Abstract: A signal processing transformation (wavelet, Fourier, discrete cosine) is applied to a digital image on a mobile device in order to produce a low-level information image and at least one high-level information image. The low-level image is recognizable as the digital image and is kept on the device; all other related images are deleted. The high-level information images are uploaded. The transformation is applied recursively and is dictated by a default setting, calculated from data of the mobile device, or input. To regenerate the original image the device connects to the server and downloads a set of high-level information images or all sets. The low resolution image is combined with the high-level information images using the reverse of the transformation originally applied to produce a higher resolution version of the low resolution image. Successive sets of high-level information images may be recursively applied to generate successively higher resolution images.

Abstract: This invention presents a universal framework for the discovery, understanding and matching of dress styles. In one embodiment, a computer-implemented method for building a universal dress style learner is disclosed, said method comprising: learning human skin models; detecting skin using the learned human skin models; collecting a set of dress images worn by a model; computing a set of style features based on the skin detected for at least one subset within the set of dress images; computing a set of clusters on the at least one subset of dress images based on at least one subset of the set of style features; validating the set of clusters for the at least one subset of style features; and computing a set of validated style features and a style basis.

Abstract: An image processing method includes a segmentation step that segments an input image into a plurality of regions by using an automatic segmentation algorithm, and a computation step that calculates a saliency value of one region of the plurality of segmented regions by using a weighted sum of color differences between the one region and all other regions. Accordingly, it is possible to automatically analyze visual saliency regions in an image, and a result of analysis can be used in application areas including significant object segmentation, object recognition, adaptive image compression, content-aware image resizing, and image retrieval.

Abstract: An image segmentation method segments a plurality of image features in an image. The plurality of image features are segmented non-simultaneously in succession. The segmenting of each image feature includes adapting an initial mesh to boundaries of the image feature. The segmenting of each image feature further includes preventing the adapted mesh from overlapping any previously adapted mesh.

Abstract: A solid-state image capturing element includes: a plurality of pixels arranged in rows and columns, each of which outputs an electric signal corresponding to an amount of received light; a plurality of column signal lines each of which is disposed for a corresponding one of columns of the pixels and sequentially transfers the electric signal provided from the corresponding one of the columns of the pixels; and a plurality of holding circuits each of which is disposed for a corresponding one of the column signal lines and holds the electric signal transferred via the corresponding one of the column signal lines. Each of the holding circuits includes a circuit element including an input capacitance, and holds the electric signal in the input capacitance.

Abstract: A method for deriving a blur kernel from a blurred image is provided herein. The method may include the following steps: obtaining a blurred image B, being a product of a blur kernel k applied to an original image I; calculating f?(x)=Rd*P?(B)(x) for every angle ?, wherein R denotes an autocorrelation operator, P? denotes a projection operator of based on angle ?, and d denotes a one dimensional differentiation filter; estimating spectral power of the blur kernel based on a given support parameter; estimating the blur kernel k using a phase retrieval algorithm, based on the estimated spectral power of the blur kernel; updating the support parameters; and repeating the estimating of the spectral power, the estimating of the kernel and the updating of the support parameters in an iterative, to yield the blur kernel.