Quanta Computer Incorporated

Tung-Lin Hsieh

Hsin-Hung Lee

Yu-Wen Huang

Hsu-Hung Chen

Chin-Kang Chang

Yung-Sheng Hsu

Ming-Horng Shiu

Yao-Shun Tseng

Wan-Ching Lee

Yun-Cheng Liu

Ching-Chun Chiang

Yi-Ming Huang

I-Ming Huang

The invention provides an image processing apparatus for processing an interlaced video which includes a judging module, a determining module and a processing module. The judging module is used for judging if a pixel in the kth frame among P frames of the interlaced video relates to a moving object. If the result judged by the determining module is YES, the determining module determines one between two pixels adjacent to the judged pixel in the frame as an edge pixel relative to an edge of the moving object. The first processing module is used for calculating a gray scale of the edge pixel determined by the determining module in an average way.

Image processing apparatus and method for processing interlaced video

The invention discloses a method for displaying a stereoscopic image, wherein the stereoscopic image includes a first-eye image and a second-eye image. The method is to firstly calculate a shift of the first-eye image with respect to the second-eye image. Then, the method moves the first-eye image for a length of a shift. Afterward, the method outputs the moved first-eye image and the second-eye image to display the stereoscopic image. Thereby, the parallax of the stereoscopic image is adjusted, so as to enhance the synthesizing effect of the stereoscopic image created.

Method for displaying stereoscopic image

The invention discloses an image processing apparatus for improving the definition of an input image. The input image consists of a plurality of pixels, and the pixels are divided into an edge portion and a background portion. The image processing apparatus includes a compound operating unit, a sharpness processing unit, and an edge detecting unit. The compound operating unit is used for generating a noise-eliminated image by subjecting the input image to an open-close process and a close-open process. The sharpness processing unit is used for generating an enhanced image by subjecting the input image to a sharpness process. The edge detecting unit is used for receiving the noise-eliminated image and the enhanced image and determining whether each pixel of the input image belongs to the edge portion or the background portion, so as to selectively output the gray level of each pixel of the enhanced or noise-eliminated image.

Image processing apparatus and method of the same

This invention discloses an image processing apparatus comprising a filter module, an edge detection module, and a processing module. According to where each pixel locates in an image block, the filter module is used to perform the smooth processing on each pixel to generate a second gray level corresponding to each pixel. The edge detection module is used to determine each pixel to be an edge pixel or a non-edge pixel according to the first gray level and the second gray level of each pixel. The processing module is used to calculate a third gray level of each edge pixel according to a weight, the first gray level, and the second gray level; to calculate a fourth gray level of each non-edge pixel according to the weight, the first gray level, and second gray level, and to output all of the third and fourth gray levels.

Image processing apparatus and method for reducing blocking effect and Gibbs effect

An image processing apparatus is disclosed. The image processing apparatus comprises a dividing module, a calculating module, a judging module and an adjusting module. The dividing module is used for dividing an image into a plurality of sub-images. The calculating module is used for generating a lightness threshold of the image. The judging module is used for comparing an original average lightness of a target sub-image among the plurality of sub-images with the lightness threshold. The adjusting selectively increases the original average lightness of the target sub-image according to the first judging module.

Image processing apparatus and method for adjusting lightness of image

The invention provides a portable computer system for capturing a target image related to an item. The portable computer system comprises a base, a cover, an image capturing module, and a lightness adjusting module. The cover is pivotally connected to the base, and comprises a panel. According to the size of the item, the cover rotates with respect to the base to project the light radiated from the panel onto the base. The image capturing module is used for rotating with respect to the cover to capture a reference image according to the size of the item. The lightness adjusting module is used for adjusting the lightness of the panel according to the reference image. After the lightness of the panel is adjusted, the item is deposed on the base, and the image capturing module captures the target image related to the item.

Portable computer system and operating method thereof

The invention provides an adjusting apparatus and a method thereof for adjusting a 3D image constituted by a plurality of interlaced first-eye-viewed image lines and second-eye-viewed image lines to be outputted to a display panel. However, in practice, there is a leakage problem in a pair of glasses for viewing the 3D image. Therefore, the invention solves the leakage problem by matching a plurality of pre-stored leakage values and then generating a proper output with a corrective calculation.

The invention discloses a noise reduction device for adjusting gray levels of a video sequence to reduce noises. The noise reduction device of the invention includes a motion detector and a first noise reduction module. The motion detector is used for determining whether an inputted pixel is a motion pixel or a static pixel. If the pixel is a motion pixel, the first noise reduction module directly outputs the pixel without adjustment. If the pixel is a static pixel, the first noise reduction module adjusts the gray level of the pixel according to previous image frame. Because the invention only stores previous image frame, and does not utilizes multiple continuous image frames to adjust the present image frame. Therefore, the display system of the invention needs only to be installed with one buffer, and hardware resource can be further saved.

Noise reduction device and method

This invention relates to an apparatus for processing an input image including M input pixels. Each of the M input pixels respectively has an input gray scale. The apparatus includes a gain generating module, a contrast enhancing module, and a Gamma adjusting module. The gain generating module generates a contrast gain and a minimum input gray scale in accordance with the input gray scales of the M input pixels. The contrast enhancing module adjusts the input gray scales in accordance with the contrast gain and the minimum input gray scale, to generate an intermediate image. The intermediate image includes M intermediate pixels, and each of the M intermediate pixels respectively has an intermediate gray scale. The Gamma adjusting module adjusts the intermediate gray scales lower than a first threshold in accordance with the contrast gain and outputs the adjusted intermediate image as an output image.

Method and apparatus for adjusting contrast of image

The invention discloses a gamma adjusting apparatus for adjusting the gray level of each pixel of an image signal. The gamma adjusting apparatus includes a measuring unit, a first processing unit, a second processing unit, and a third processing unit. The measuring unit measures the lightness of N reference gray levels. The first processing unit normalizes the lightness of the N reference gray levels to generate N normalized reference values. The second processing unit compares the N normalized reference values with a standard gamma curve to generate N adjusted gray levels. According to the N reference gray levels and the N adjusted gray levels, the third processing unit sets an adjusting rule. According to the adjusting rule, the gamma adjusting apparatus is capable of adjusting the gray level of each pixel of the image signal to comply with the standard gamma curve.

Gamma adjusting apparatus and method of the same

The invention discloses a method for the transforming of a 2D image into a 3D image. The method comprises the steps of: (a) selecting an object of 2D image; (b) setting a base line in the 2D image; (c) base on the base line, judging whether the object is located on the foreground or background of the 2D image; (d) offering a displacement to the object; (e) moving the object with the displacement to generate a plurality of continuous images; and (f) sequentially outputting each of the continuous images to generate the 3D image. Accordingly, after the user selects an object of 2D image, the method of the invention will automatically transform the 2D image into the 3D image.

Method capable of automatically transforming 2D image into 3D image

An apparatus for processing an input image including M image units is provided. Each of the M image units respectively includes N pixels. Each of the pixels respectively has an original gray scale. The apparatus includes a converting module, a gain generating module, and a contrast enhancing module. The converting module is used for generating M luminances. Based on the original gray scales of the N pixels in the ith image unit among the M image units, the converting module generates the ith luminance among the M luminances. A maximum luminance and a minimum luminance are generated based on the M luminances. The gain generating module generates a contrast gain and a minimum gray scale based on the maximum luminance and the minimum luminance. Based on the contrast gain and the minimum gray scale, the contrast enhancing module adjusts the original gray scales of the pixels in the input image.

The invention discloses an image processing apparatus and method thereof capable of preserving a great deal of light and dark details, so as to improve the contrast of each image. Furthermore, when calculating the value of gray level, the gray levels may be divided into equal parts, each of which includes four gray levels. Accordingly, the range of gray level is changed from 0&#x2dc;255 to 0&#x2dc;63, such that the hardware resources can be saved.

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Jhongli, Taiwan

Tung-Lin Hsieh