Altek Corporation

Altek Semiconductor Corp.

Chung-Ta Wu

Che-Lun Chuang

Hong-Long Chou

Shih-Yuan Peng

Hsin-Te Wang

Yu-Chen Huang

Che-Hung Lin

Yen-Ping Teng

Yen-Chi Wang

An image pick-up apparatus and a progressive auto-focus method thereof are provided. The image pick-up apparatus includes an optical system, an image sensor, a focus circuit and a lens control circuit. In the method, an image is captured by using the image sensor and whether the optical system is in focus when the image sensor captures the image is determined by the focus circuit. If the optical system is out of focus, an in-focus location of the optical system and an in-focus distance for moving the optical system to the in-focus location are calculated by the focus circuit. The in-focus distance is transformed into a shorter progressive distance and the optical system is controlled by the lens control circuit to move by the progressive distance. Aforesaid steps are repeated until the optical system is in focus and the image captured by the image sensor is output.

Image pick-up apparatus and progressive auto-focus method thereof

A method of multi-frame image noise reduction suitable for an image-capturing device includes following steps: obtaining a current frame and multiple reference frames; defining a mask and a target point in the mask; judging whether the target point pixel of the current frame is on an edge according to an edge map of the frame; when the pixel is on the edge, using the pixels in the reference frames on the edge to calculate a replacement result; when the target point pixel is not on the edge, using the pixels in the reference frames surrounding the target point to calculate a replacement result; after that, generating a pixel corresponding to the position of the target point in an output image according to the replacement result; further, moving the mask and going back to judge whether the pixel of the target point of the current frame is on the edge.

Method of multi-frame image noise reduction

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.

Digital image processing device and processing method thereof

The present invention discloses an image sharpness processing apparatus and an image sharpness processing method thereof. The apparatus comprises an image capturing module and a processing module. The image capturing module captures an image having a plurality of pixels. The processing module gains a characteristic value corresponding to each pixel by analyzing each pixel in the image. The processing module calculates a first sharpening compensation value and a second sharpening compensation value of each pixel by using a first sharpening algorithm and a second sharpening algorithm respectively, and determines a weight value of the first sharpening algorithm and the second sharpening algorithm by the characteristic value. The processing module calculates a third sharpening compensation value according to the first sharpening compensation value and the second sharpening compensation value, so as to adjust the sharpness of the image.

Image sharpness processing apparatus and image sharpness processing method

A processing method for image interpolation is provided. In the method, a contour containing a destination pixel and a plurality of contour pixels is produced and detected by using an edge detection method for a selected area in an original image. Next, two extreme points are identified from the contour pixels by judging the changing trend of brightness value of the contour pixels on the contour. Then using the changing trend and two extreme points determines whether the destination pixel is located at a transition area or a non-transition area. If the destination pixel is located at the non-transition area, an interpolation adjust value is calculated according to the brightness values of the two extreme points and the brightness value of the destination pixel. An interpolation result of the destination pixel is obtained by performing the interpolation on the selected area according to the interpolation adjust value.

Processing method for image interpolation

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.

Image processing device and processing method thereof

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.

Image processing method and image processing apparatus

A method for analyzing object motion in multi frames adapted to an image capturing device is provided. Firstly, a plurality set of first sum of absolute difference (SAD) are obtained according to noise of the image capturing device under a plurality of light settings. Next, two frames are captured under a picturing light setting of the light settings. Then, a plurality of second SAD between the two frames are calculated. Afterwards, a plurality of object block within vein tracking of the object are found. Next, a local motion vector of each object block is respectively calculated according to the second SAD. Then, a first reliability of each object block is respectively calculated according to the second SAD and the set of the first SAD corresponding to the picturing light setting. Afterwards, the local motion vectors are estimated according to the first reliability to obtain a global motion vector.

Method for analyzing object motion in multi frames

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.

Image processing device and processing method for generating a super-resolution image

A method for generating an all-in-focus image is provided. In the method, a plurality of frames including one source frame and several reference frames captured at different focus lengths are obtained. After performing a motion compensation procedure on the frames, for each pixel position belonging to an edge, a characteristic similarity between the source frame and each reference frame is calculated respectively to accordingly select a plurality of qualified reference frames among the reference frames. The method further includes determining a first type color space component of the pixel position within an all-in-focus image by an edge sharpness corresponding to the pixel position within each of the source frame and the qualified reference frames, and determining a second type color space component of the pixel position within the all-in-focus image by an color brightness corresponding to the pixel position within each of the source frame and the qualified reference frames.

Method for generating all-in-focus image

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.

Method for removing color fringe in digital image

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.

A sharpness processing method and system for a digital image are applied to an image capturing device for capturing a raw image. The method includes the steps. An image processing procedure is performed on the raw image to generate a registered image. A first sharpness enhancement table and a second sharpness enhancement table respectively sharpness attenuation at an outer-edge region and a central region of the registered image are loaded, and a range between the outer-edge region and the central region is defined as a plurality of critical regions. A sharpness enhancement weight table is loaded, and weight values of each critical region respectively corresponding to the first sharpness enhancement table and the second sharpness enhancement table are searched, for obtaining a sharpness enhanced value of each critical region. An image sharpness processing procedure is performed on the critical region, for correct the registered image into a digital image.

Sharpness processing method and system for digital image

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. The compensation method includes capturing a uniform color block image; calculating horizontal compensation coefficients of a plurality of horizontal segments of the color block image; performing a linear interpolation process on the horizontal compensation coefficients to generate corresponding horizontal interpolation coefficients, and calculating determination horizontal correction coefficients corresponding to all the horizontal segments, respectively; calculating vertical compensation coefficients of a plurality of vertical segments; multiplying the determination horizontal correction coefficients by the vertical compensation coefficients, respectively, so as to obtain a color shading compensation coefficient of each segment, respectively; and multiplying an average luminance value of each segment by a corresponding color shading compensation coefficient, respectively, thus compensating for color shading in the color block image.

Compensation method for alleviating color shading in digital image

A false color suppression method for a digital image is described. The method is performed in a digital camera, for suppressing the false color of the digital image shot by the digital camera. The method includes separating a luminance part and a chrominance part of a digital image; extracting the chrominance part, and calculating a first color gamut component and a second color gamut component in the chrominance part; setting a critical value according to a photosensitivity during shooting by the digital camera; performing a corresponding pixel uniformization action on the pixel according to a relation between a difference between the pixel and adjacent neighboring pixels and the critical value respectively for the first color gamut component and the second color gamut component; and combining the uniformized chrominance part and the luminance part of the digital image to a suppressed image.

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Taichung, Taiwan

Chung-Ta Wu