Abstract: An image compression/decompression device and a method thereof are provided. In the method, a first array is generated according to an input image array, and further, a second array is generated by performing an edge detection algorithm according to the input image array. Besides, a plurality of elements of a third array is generated according to the first array. Furthermore, a group of elements of the third array is selected according to the second array. In addition, an average value of the group of elements is computed to obtain an element of an output image array. Each element of the input image array and the third array is M bits, and each element of the first array is N bits, wherein M and N are natural numbers, and M is larger than N. Thereby, the quality of a decompressed image is improved.

Abstract: The compression algorithm presented here is intended for the types of digital images acquired by solar system exploring spacecraft and missions, but can be utilized for all types of sequential data. It is lossy, but results in images whose Peak Signal to Noise Ratio remains in excess of 30 decibels, considered to be the threshold of being indistinguishable from the original image. Currently employed spacecraft compression algorithms are probabilistic, and are costly in terms of spacecraft weight, power, computation, memory and volume requirements. The algorithm submitted is non-probabilistic, requires less than 1 kilobyte of programming and memory space for computations, has low power and weight requirements, and can reside on a single Application Specific Integrated Circuit (ASIC), and. It processes utilizing addition and comparison only—no advanced numerical solution generation, function generation by series expansion, or other mathematical processing is required.

Abstract: A method for detecting a redeye defect in a digital image containing an eye comprises converting the digital image into an intensity image, and segmenting the intensity image into segments each having a local intensity maximum. Separately, the original digital image is thresholded to identify regions of relatively high intensity and a size falling within a predetermined range. Of these, a region is selected having substantially the highest average intensity, and those segments from the segmentation of the intensity image whose maxima are located in the selected region are identified.

Abstract: An object of the invention is to provide an image processing device with which color processing can be adjusted with ease. An image processing device (10) is provided with a processing degree setting portion (18), a profile creation portion (15), and a color processing execution portion (16). The processing degree setting portion (18) sets a target degree of color processing with regard to at least two properties of a plurality of properties of an image signal (d2), as a single target processing degree (d8). The profile creation portion (15) creates a color transformation profile for performing color processing at the target processing degree (d8), based on the target processing degree (d8) that has been set by the processing degree setting portion (18) and a plurality of base color transformation profiles for performing the color processing to differing degrees.

Abstract: When generating output image data represented by a reduced number of gray levels from gray level image data, an image processing apparatus subtracts a pixel value of a selected pixel from a pixel value of adjacent pixel, amplifies the reduced value obtained by the subtraction, adds the amplified value to a numerical value in a numerical matrix, and finds a pixel value in the output image data represented by a reduced number of gray levels of pixel values, based on a value obtained by further adding a value obtained by adding the amplified value to the numerical value in the numerical matrix to a predetermined value.

Abstract: A method and apparatus for encoding and decoding image data. The method of encoding image data includes spatially predicting pixel values of a one-dimensional block of an image using blocks spatially adjacent to the one-dimensional block or temporally predicting the pixel values of the one-dimensional block using a temporally previous frame; transforming and quantizing the pixel values of the one-dimensional block; and generating bit streams for a one-dimensional conversion block when the transformed and quantized one-dimensional block is defined as the one-dimensional conversion block. Therefore, since the method and apparatus encode and decode image data in one-dimensional block units, real-time encoding and decoding can be achieved. In addition, compression efficiency can be enhanced while minimizing visual degradation of image quality.

Abstract: Methods, systems and apparatuses for modeling high resolution images which significantly shortens computation time and reduces image artifacts, as compared to known methods. Embodiments implement a look-up table, to compute once and store the point spread functions for various points of an image. During modeling of the optical system, previously stored point spread functions may be used to determine the point spread function for a specified point using a weighted interpolation of the point spread functions that have been stored for nearby points.

Abstract: Images that are contained within documents are compressed to reduce the file size of the document. The compression may occur such that compression steps occur to the image automatically. The compression steps performed are determined based on the information available about the images in a document. The information is used to determine whether or not the image should be compressed as well as what compression method is used.

Abstract: An image processing apparatus includes the following elements. An image data obtaining unit obtains image data. A sampling unit samples the image data. A statistic value determining unit determines a statistic value based on statistic information in a histogram with respect to a grayscale value of image data that is obtained by performing rough quantization and linear interpolation on the sampled image data. A correction-amount determining unit determines a correction amount to be used for image processing based on the statistic value. An image processing unit performs the image processing according to the correction amount.

Abstract: In a liquid-crystal-driving image processing circuit that encodes and decodes image data to reduce the frame memory size, the present invention has the object of providing a liquid-crystal-driving image processing circuit capable of correcting image data accurately and applying appropriately corrected voltages to the liquid crystal without being affected by encoding or decoding errors, even when moving images are input.

Abstract: An imaging apparatus that records, on a recording medium, a moving image captured using a solid-state imaging device as stream data, is disclosed. The apparatus includes: an image encoding section that encodes data of the captured moving image with a unit of an image group being a sequence of images of a fixed number of frames; an input detection section that detects a recording stop request to stop recording of the stream data including the moving image data being an encoding result of the image encoding section onto the recording medium; and a recording control section that controls a recording operation of the stream data onto the recording medium such that, when the recording stop request is detected by the input detection section, the image group located immediately before the image group including an image captured at the time of detection is the last image group.

Abstract: The differential value of the adjacent pixels is calculated firstly and is coded by a VLC coding. The VLC coding includes codes representing the Quotient and Remainder with a marker bit inserted in between. The divider is predicted with no code in the coded data stream. If three pixel components are presented in the same clock time, three VLC encoders and three VLD decoders are applied to encode and decode one pixel at a time. During encoding, both Remainder and Quotient of the same pixel component are encoded in parallel followed. During decoding, both Remainder and Quotient of the same pixel component are decoded in parallel and the results of the first pixel component are used a reference to decode the second pixel component which adopts the same decoding procedure and the decoded results of the second pixel component is used as reference to decode the third pixel component.

Abstract: In one embodiment, an image processor may be used to manipulate a hue value to obtain an updated hue value, manipulate a saturation value to obtain an updated saturation value based on the updated hue value and the saturation value, and if updated pixel data including the updated hue value and the updated saturation value is an illegal value, adjust a luma value. Other embodiments are described and claimed.

Abstract: Disclosed herein is a method of performing robust white balance. The method includes a first process of dividing an input image into blocks, a second process of selecting blocks having higher color errors, and calculating average RGB values of the selected blocks, a third process of selecting a specific top percentage of bright blocks, and calculating the average RGB values of these selected blocks, a fourth process of calculating average RGB values through color clustering, a fifth process of converting the average RGB values into CIE xyY color space, a sixth process of calculating the Euclidean distances between the x and y values of standard light sources in a color space and the x and y values of the average RGB values in CIE xyY color space, and selecting an average RGB value having the shortest Euclidean distance (Ed), and a seventh process of calculating white balance gain values using the selected average RGB value, and correcting the input image using the balance gain values.

Abstract: A determining unit extracts similar-characteristic areas in image data and determines a type of the characteristics of image data of each of the similar-characteristic areas, a first correcting unit corrects a characteristic of image data in each of the similar-characteristic areas to a predetermined data characteristic according to the type of the characteristics of image data of that similar-characteristic area thereby obtaining characteristics-corrected image data, a storage unit stores therein the image data and the characteristics-corrected image data, a second correcting unit corrects a characteristic of the image data and the characteristics-corrected image data stored in the storage unit to a destination-specific characteristic that corresponds to a destination to which image data is to be output, and an output unit outputs the image data having the destination-specific characteristic to the destination.

Abstract: A method of labeling pixels in an image is described where the pixel label is selected from a set of three or more labels. The pixel labeling problem is reduced to a sequence of binary optimizations by representing the label value for each pixel as a binary word and then optimizing the value of each bit within the word, starting with the most significant bit. Data which has been learned from one or more training images is used in the optimization to provide information about the less significant bits within the word.

Abstract: An image processing circuit for driving a liquid crystal that encodes and decodes image data to reduce the size of the frame memory that, when it quantizes (45) each block of image data in the current frame and outputs encoded data, selects (44) a mean value on the basis of the dynamic range of each unit block and adjusts the amount by which the image data is reduced (53). This type of control enables it to reduce the amount of image data that must be temporarily stored in the delay circuit (5), so the size of the frame memory constituting the delay circuit can be reduced while minimizing the encoding error that occurs in the encoder (4). Consequently, the image data can be corrected accurately and appropriate voltage corrections can be applied to the liquid crystal without the effects of coding and decoding errors.

Abstract: A system or the like capable of detecting lane marks more accurately by preventing false lane marks from being erroneously detected as true lane marks. A vehicle-use image processing system (100) allows a “road surface cluster” to be extracted from the “histogram” of luminance of each pixel in a “reference area” in a road surface image. Among “primary lane mark candidates,” those that overlap the “reference area” are detected as “secondary lane mark candidates.” Among the “secondary lane mark candidates,” those that have “luminance parameter” values falling within the luminance range of the “road surface cluster” are not detected as true lane marks. Thereby, lane marks are prevented from being erroneously detected (erroneous detection). This allows only lane marks to be detected more accurately.

Abstract: Systems and methods for representing high dynamic range data in compressed formats with a fixed size block allow high dynamic range data to be stored in less memory. The compressed formats use 8 bits per pixel. A first compressed format includes two endpoint values and compressed indices for the pixels in the block. A second compressed format includes four endpoint values, a partition index that specifies a mask for each pair of the four endpoint values, and compressed indices for the pixels in the block. The two formats may be used for various blocks within a single compressed image and mode bits are included to distinguish between the two formats. Furthermore, each endpoint value may be encoded using an endpoint compression mode that is also specified by the mode bits. Compressed high dynamic range values represented in either format may be efficiently decompressed in hardware.

Abstract: A hue segmentation system and method thereof suitable for image devices are described. First, a plurality of hue segments are generated based on color data of a plurality of colors in a color gamut. Then, the area difference between the hue segments and the color gamut is calculated. If the area difference is greater than a predetermined value, the hue segmentation system searches at least one vertex among the hue segments to divide the segments for generating a plurality of additional hue segments. The above-mentioned steps are performed repeatedly until the area difference is less than the predetermined value. Thus fewer hue segments indicate the color gamut of color processing of the image devices to effectively decrease calculation times and save required memory.