Abstract: An image correcting method includes: (a) acquiring original image information to be corrected; (b) setting a confirmation range for confirming an effect of a correction; (c) producing corrected image information; and (d) displaying, on an image display section, an original image based on the original image information and a corrected image based on the corrected image information. The confirmation range is set based on the original image information. The corrected image information is produced by correcting the original image information within the confirmation range.

Abstract: An image capturing device is adapted to capture an object image and to generate an image data. Each of a plurality of image capturers is adapted to perform an image capturing of a part of the object image and to generate a partial image data which constitutes a part of the image data based on the part of the object image. Each of the image capturers has an optical axis. A detector is operable to detect movement of each of the image capturers in a direction perpendicular to the optical axis during the image capturing and to generate movement data based on the detected movement, for each of the image capturers. A processor is operable to correct the partial image data so as to compensate the movement during the image capturing based on the movement data.

Abstract: A method and apparatus of correcting blur in a motion blurred image includes estimating the direction of blur in the motion blurred image based on edge response of the motion blurred image over a set of discrete directions and over subgroups of the discrete directions. The extent of blur in the motion blurred image is also estimated. An initial guess image based on the motion blurred image is generated and the guess image is blurred as a function of the estimated blur direction and blur extent. The blurred guess image is compared with the motion blurred image to generate an error image. The error image is blurred and weighted and then combined with the initial guess image thereby to update the guess image and correct for blur.

Abstract: In the present invention, an image evaluation method includes: (a) a step of acquiring image information to be evaluated; (b) a step of setting an evaluation area for the acquired image information, the evaluation area being smaller than an area corresponding to the image information; (c) a step of obtaining an individual evaluation on the acquired image information; (d) a step of obtaining another individual evaluation on the acquired image information; and (e) a step of obtaining a comprehensive evaluation based on the individual evaluation and the other individual evaluation. Herein, the individual evaluation is obtained by individually evaluating a predetermined item in the set evaluation area. The other individual evaluation is obtained by individually evaluating another predetermined item.

Abstract: A method, apparatus and image capture device for limiting motion blur during capture of an image predetermines a relationship between movement of the image capture device, time and blur extent. A rate of movement of the image capture device is obtained and used in conjunction with the determined relationship and a blur extent limit as a basis for obtaining a maximum exposure time for the image capture device in order to limit blur extent. On the basis of the maximum exposure time obtained and a required image brightness, the image capture device is configured, and then an image is captured by the image capture device. Once the image has been captured, due to the possibility of under-exposure from having limited the exposure time, the image is processed as required to increase its intensity.

Abstract: A system for displaying a digital video sequence includes a graphics processing unit (GPU) and a display device. The GPU receives and modifies the digital video sequence to compensate for perceived blur based on motion between frames of the digital video sequence. The display device displays the modified digital video sequence. A method and computer readable medium having computer readable code is also provided.

Abstract: A method and system for displaying frames on a hold-type display to reduce perceived blur are disclosed. One example method includes detecting a parameter associated with an object in an input frame and filtering the input frame to generate at least two filtered sub-frames based on the parameter. The filtered sub-frames are then inserted in place of the input frame in a frame sequence and output to a display. The parameter associated with the object may indicate a magnitude and direction of the object's movement in a sequence of frames including the input frame.

Abstract: A method and system for calculating an overdrive parameter for a liquid crystal within an LCD device to compensate for temperature variations. An example system includes a temperature sensor for measuring an ambient temperature near a liquid crystal and a memory for storing a lookup table containing a plurality of overdrive parameters. Each overdrive parameter corresponds to a graylevel transition between a previous frame and a current frame, and represents a level at which a liquid crystal is driven in order to achieve a desired response time for the graylevel transition at a reference temperature. A processor extracts the appropriate overdrive parameter from the lookup and calculates an adapted overdrive parameter that adjusts for the difference between the measured ambient temperature and the reference temperature.

Abstract: An evaluation on image information is indicated before operating a shutter operating section. For example, a method of evaluating image information includes: (a) a step of converting an optical image of an object to be photographed into electrical image information; (b) a step of evaluating the image information that has not yet been stored in a non-volatile memory, wherein the image information is evaluated in a state in which a shutter operating section, on which a predetermined operation is performed when storing the image information in the non-volatile memory, is not being subjected to the predetermined operation; and (c) a step of outputting an evaluation result.

Abstract: A method, apparatus and image capture device for limiting motion blur during capture of an image predetermines a relationship between movement of the image capture device, time and blur extent. A rate of movement of the image capture device is obtained and used in conjunction with the determined relationship and a blur extent limit as a basis for obtaining a maximum exposure time for the image capture device in order to limit blur extent. On the basis of the maximum exposure time obtained and a required image brightness, the image capture device is configured, and then an image is captured by the image capture device. Once the image has been captured, due to the possibility of under-exposure from having limited the exposure time, the image is processed as required to increase its intensity.

Abstract: A method for compensating for perceived blur due to motion between a current frame and a previous frame of a digital video sequence comprises estimating a motion vector between the frames for each of a plurality of pixel blocks in the current and previous frames. A cluster motion vector is then estimated for each of a plurality of clusters of the motion vectors based on one of vectors in each cluster and motion vectors in proximate clusters. The cluster motion vector of its corresponding cluster is allocated to each pixel in the current frame. An initial guess frame is generated based on the current frame and pixels in the guess frame are blurred as a function of their respective allocated cluster motion vectors. Each blurred pixel is compared with a respective pixel in the current frame to generate an error pixel for each respective pixel.

Abstract: An image correcting method includes: (a) acquiring original image information to be corrected; (b) setting a confirmation range for confirming an effect of a correction; (c) producing corrected image information; and (d) displaying, on an image display section, an original image based on the original image information and a corrected image based on the corrected image information. The confirmation range is set based on the original image information. The corrected image information is produced by correcting the original image information within the confirmation range.

Abstract: In the present invention, an image evaluation method includes: (a) a step of acquiring image information to be evaluated; (b) a step of setting an evaluation area for the acquired image information, the evaluation area being smaller than an area corresponding to the image information; (c) a step of obtaining an individual evaluation on the acquired image information; (d) a step of obtaining another individual evaluation on the acquired image information; and (e) a step of obtaining a comprehensive evaluation based on the individual evaluation and the other individual evaluation. Herein, the individual evaluation is obtained by individually evaluating a predetermined item in the set evaluation area. The other individual evaluation is obtained by individually evaluating another predetermined item.

Abstract: The present method of evaluating image information, includes: extracting, from image information to be evaluated, a plurality of edge pixels located in a boundary of an image expressed by the image information; calculating, for each of the edge pixels, a number of pixels that include the edge pixel targeted for calculation, that exist in the boundary, and that are arranged in a direction intersecting with the boundary; and performing out-of-focus blurring evaluation of the image information on the basis of the number of pixels that exist in the boundary and a number of the edge pixels.

Abstract: An image capturing device is adapted to capture an object image and to generate an image data. Each of a plurality of image capturers is adapted to perform an image capturing of a part of the object image and to generate a partial image data which constitutes a part of the image data based on the part of the object image. Each of the image capturers has an optical axis. A detector is operable to detect movement of each of the image capturers in a direction perpendicular to the optical axis during the image capturing and to generate movement data based on the detected movement, for each of the image capturers. A processor is operable to correct the partial image data so as to compensate the movement during the image capturing based on the movement data.

Abstract: An evaluating method of image information acquires image information, performs camera shake evaluation of the image information by determining a camera shake direction on the basis of the image information, and performs out-of-focus evaluation of the image information by using information concerning a camera shake direction determined in the camera shake evaluation.

Abstract: The technique of the invention calculates an edge gradient magnitude a(x,y) at each pixel position (x,y) and an edge width w(x,y) from luminance values of an object image, and computes an out-of-focus evaluation value M(x,y) at each pixel position (x,y) from the calculated edge gradient magnitude a(x,y) and edge width w(x,y). The technique then divides the object image into a preset number of blocks, determines a representative out-of-focus evaluation value Y(m,n) in each block, and compares the representative out-of-focus evaluation value Y(m,n) with a preset threshold value for block classification to categorize each block as an in-focus block or an out-of-focus block. The technique eventually determines the object image as in-focus or out-of-focus, based on the total number of blocks included in in-focus block areas, the total number of blocks included in out-of-focus block areas, and the relative positions of the in-focus block areas and the out-of-focus block areas to the whole image.

Abstract: An evaluation on image information is indicated before operating a shutter operating section. For example, a method of evaluating image information includes: (a) a step of converting an optical image of an object to be photographed into electrical image information; (b) a step of evaluating the image information that has not yet been stored in a non-volatile memory, wherein the image information is evaluated in a state in which a shutter operating section, on which a predetermined operation is performed when storing the image information in the non-volatile memory, is not being subjected to the predetermined operation; and (c) a step of outputting an evaluation result.

Abstract: The technique of the invention converts an object RGB image into an image in a YIQ color space, calculates a luminance variation at each target pixel from Y channel values of the target pixel and an adjacent pixel adjoining to the target pixel, and computes a smoothness degree of luminance variation at the target pixel as summation of absolute values of differences between luminance variations at the target pixel and adjacent pixels. A block noise evaluation value B is obtained as a ratio of an average smoothness degree ave(psx), ave(psy) of luminance variation for boundary pixels located on each block boundary to an average smoothness degree ave(nsx), ave(nsy) of luminance variation for inner pixels not located on the block boundary. The block noise evaluation value B closer to 1 gives an evaluation result of a lower level of block noise, whereas the block noise evaluation value B closer to 10 gives an evaluation result of a higher level of block noise.

Abstract: A method and apparatus of correcting blur in a motion blurred image includes estimating the direction of blur in the motion blurred image based on edge response of the motion blurred image over a set of discrete directions and over subgroups of the discrete directions. The extent of blur in the motion blurred image is also estimated. An initial guess image based on the motion blurred image is generated and the guess image is blurred as a function of the estimated blur direction and blur extent. The blurred guess image is compared with the motion blurred image to generate an error image. The error image is blurred and weighted and then combined with the initial guess image thereby to update the guess image and correct for blur.