Abstract: The invention is directed to an image processing device and a processing method thereof. The image processing device comprises an image calibration module estimating multiple local motions and global motions of unselected images relative to a target image and performing multiple motions calibrations so as to generate multiple calibrated images, a moving-object detection module determining if a difference value between each of the local motions and the corresponding global motions is greater than a threshold value and if a pixel difference value between each pixel point of the target image and each pixel point of the calibrated images is greater than a predetermined difference value so as to generate multiple object motion pointers, and an image blending module performing a calculation on each pixel point of the target and calibrated images based on the object motion pointers so as to generate a super-resolution image.

Abstract: A device and a method for reducing a smear effect. The device comprises an image sensing module and a smear reduction module. The image sensing module captures an image and optical black data generated from the optical area of the image sensing module. The smear reduction module searches the optical black data generated in the lower boundary of the optical black area corresponding to which generated in the upper boundary of the optical black area according to coordinates of the optical black data. Thereby, the smear reduction module can compute an offset line representing an offset of the optical black data, and the smear reduction module compensates the smear effect occurring in the image.

Abstract: An image processing device and the processing method thereof are provided. The device includes an image correcting module, an object-motion detection module and an image blending module. The image correcting module estimates a plurality of local motions of the non-selected images relative to the target image and a plurality of global motions, and performs a plurality of motion corrections to generate a plurality of corrected images. The object-motion detection module judges whether or not the difference between each of the local motions and the corresponding global motion is greater than a threshold value to generate a plurality of object-motion indicators. The image blending module performs an arithmetic operation on each pixel of the target image and each pixel of the corrected images according to the object-motion indicators so as to generate a super-resolution image.

Abstract: A method for removing color fringe is presented. Separated luminance and chrominance (YCbCr) signals of a digital image are analyzed through specific color detection, luminance detection, and gradient color detection, so as to determine whether color fringe occurs to each pixel in the digital image, thereby correcting pixels with color fringe.

Abstract: A method for removing color fringe is presented. First, detection and correction of color fringe are performed on an original-size image and a small-size image respectively, so as to generate respective corrected images and corresponding color fringe maps. Then, the corrected small-size image and its corresponding color fringe map are enlarged to the same resolution as the original-size image. Finally, the two corrected images are blended according to the respective corresponding color fringe maps.

Abstract: A digital image processing device and processing method thereof are provided. The device includes a digital image capturing module, an image enlarging module, an image correcting module, and an image blending module. The digital image capturing module captures a plurality of first resolution images. The image enlarging module enlarges the first resolution images and produces a plurality of second resolution images. The image correcting module selects a target image and produces a plurality of corrected images. The image blending module performs direction gradient operation on each of the pixels of the target and corrected images and produces a plurality of gradient differential values. The image blending module performs a weighting sum operation on each of the pixels of the target and corrected images and produces a third resolution images.

Abstract: An image processing device and the processing method thereof are provided. The device includes an image correcting module, an object-motion detection module and an image blending module. The image correcting module estimates a plurality of local motions of the non-selected images relative to the target image and a plurality of global motions, and performs a plurality of motion corrections to generate a plurality of corrected images. The object-motion detection module judges whether or not the difference between each of the local motions and the corresponding global motion is greater than a threshold value to generate a plurality of object-motion indicators. The image blending module performs an arithmetic operation on each pixel of the target image and each pixel of the corrected images according to the object-motion indicators so as to generate a super-resolution image.

Abstract: An image processing method and an image processing apparatus are provided. In the image processing method, each of a plurality of original images is divided into K bands, where K is a positive integer greater than or equal to 1. A plurality of local motions of each band in any two adjacent of the original images are calculated, and a global motion of each band is calculated according to the local motions of the band. A horizontal component velocity and a vertical component velocity of each band are generated according to the global motion and a capturing time difference. A plurality of transformation matrixes corresponding to the bands are generated according to the horizontal component velocities, the vertical component velocities, a row readout time, and the width of a valid area. One of the two adjacent original images is transformed according to the transformation matrixes to generate a compensated image.

Abstract: A method for correcting red-eye is described. Through facial features, at least one facial region is obtained in an image, a nose position in each facial region is obtained by using a nose feature, and at least one eye position is obtained based on a relative position relation between the nose and the eyes. After a color gamut of the image is converted, a red region is obtained from the eye position, and a plurality of edges is formed by using a luminance of the color gamut on the image with the converted color gamut according to the eye feature, so as to exclude the red region out of the plurality of edges, thereby improving accuracy of the red region on the eye position. Then, the red region is covered by an iris color, so as to correct the red-eye.

Abstract: A compensation method for alleviating color shading in a digital image is adapted to correct a color shading phenomenon in a digital image that causes luminance differences between regions in the digital image.

Abstract: A method for removing color fringe is presented. Separated luminance and chrominance (YCbCr) signals of a digital image are analyzed through specific color detection, luminance detection, and gradient color detection, so as to determine whether color fringe occurs to each pixel in the digital image, thereby correcting pixels with color fringe.

Abstract: A method for removing color fringe is presented. First, detection and correction of color fringe are performed on an original-size image and a small-size image respectively, so as to generate respective corrected images and corresponding color fringe maps. Then, the corrected small-size image and its corresponding color fringe map are enlarged to the same resolution as the original-size image. Finally, the two corrected images are blended according to the respective corresponding color fringe maps.

Abstract: A compensation method for alleviating color shading in a digital image is adapted to correct a color shading phenomenon in a digital image that causes luminance differences between regions in the digital image.

Abstract: A method for correcting red-eye is described. Through facial features, at least one facial region is obtained in an image, a nose position in each facial region is obtained by using a nose feature, and at least one eye position is obtained based on a relative position relation between the nose and the eyes. After a color gamut of the image is converted, a red region is obtained from the eye position, and a plurality of edges is formed by using a luminance of the color gamut on the image with the converted color gamut according to the eye feature, so as to exclude the red region out of the plurality of edges, thereby improving accuracy of the red region on the eye position. Then, the red region is covered by an iris color, so as to correct the red-eye.