A video noise reduction system for a set of video frames that computes a first motion signal using a current frame and multiple consecutive previous frames, computes a second motion signal using the current frame and the processed preceding frame; computes the multi-frame temporal average of the current frame and multiple consecutive previous frames; computes the recursive average of the current frame and the processed preceding frame; generates a temporal filtered signal by soft switching between the multi-frame temporal average and the recursive average based on the first motion signal; applies a spatial filter to the current frame to generate a spatial filtered signal; and combines the temporal filtered signal and the spatial filtered signal based on the second motion signal to generate a final noise reduced video output signal.
Method For Detecting Grid In Block-Based Compressed Video
A grid detector detects the existence and the location of grids in DCT compressed videos. When a grid is detected in the input video, a post-processor is turned on and the de-blocking processing is applied on the grid detected by the grid detector. When no grid is detected, indicating that the input video is either an uncompressed video or an already de-blocked video, post-processing turned off to avoid degrading the picture quality. To detect grids, the grid detector: (a) computes horizontal and vertical second derivatives for all pixels of the image; (b) generates horizontal second derivative zero-crossing mask and vertical second derivative zero-crossing mask by marking the those pixels whose second derivatives have opposite signs with respect to their horizontal or vertical neighboring pixels'; (c) applies horizontal and vertical integral projections to the horizontal and vertical zero-crossing masks respectively; (d) generates the local maximum masks by locating the local maximum of the two projected 1-D signals; and (e) determines grid location by computing the positions of the local maximum masks.
Method And Apparatus For Noise Reduction Using Discrete Wavelet Transform
An improved noise reduction process by wavelet thresholding utilizes a discrete wavelet transform to decompose the image into different resolution levels. A thresholding function is then applied in different resolution levels with different threshold values to eliminate insignificant wavelet coefficients which mainly correspond to the noise in the original image. Finally, an inverse discrete wavelet transform is applied to generate the noise-reduced video image. The threshold values are based on the relationships between the noise standard deviations of different decomposition levels in the wavelet domain and the noise standard deviation of the original image.
A superior Color Transient Improvement technique is adaptive to the local image features, so that more natural color edge transition improvement can be accomplished. A gain control function is provided that depends on the local image feature so that different regions of the image can be treated differently. Further, a correction signal is controlled in such a way (by the local image feature) that neither undershoot nor overshoot occurs, eliminating the need for post-processing for undershoot/overshoot removal.
Method And Apparatus For Adjusting Color Edge Center In Color Transient Improvement
An improved method for color transient enhancement in an input video frame of pixels. The luminance value of a current pixel is compared to that of neighboring pixels. A correction value is determined and the chrominance value of the current pixel is “pushed” towards the neighboring pixel that has a luminance value closest to that of the current pixel, by adding the correction value to the current pixel's chrominance value. The original video frame is also separately processed using a CTI method, and the current pixel's corrected chrominance value is combined with the corresponding pixel in the output of the CTI processing by soft switching unit to generate an output video frame that is an enhanced version of the input video frame.
Global And Local Statistics Controlled Noise Reduction System
A global and local statistics controlled noise reduction system in which the video image noise reduction processing is effectively adaptive to both image local structure and global noise level. A noise estimation method provides reliable global noise statistics to the noise reduction system. The noise reduction system dynamically/adaptively configures a local filter for processing each image pixel, and processes the pixel with that local filter. The filtering process of the noise reduction system is controlled by both global and local image statistics that are also computed by the system.
Adaptive Bidirectional Filtering For Video Noise Reduction
A video noise reduction system for reducing video noise in a sequence of video frames. In the video noise reduction system, a temporal filter computes multiple temporal average values for the video frames in different temporal directions. A motion detector computes multiple motion signal values for the video frames in different temporal directions. Finally, a control unit selects one of the temporal average values based on the motion signal values as output.
Methods And Apparatus For Removing Blocking Artifacts Of Mpeg Signals In Real-Time Video Reception
A method for efficient removal of blocking artifacts in blocks of pixels forming a video image frame, without blurring image edges. First a current pixel is checked to determine whether it is a block boundary pixel. If the current pixel is a boundary pixel, then the “1-D central variance” is computed for horizontal, vertical and diagonal directions that cross the block boundary by using three pixels along a line centered at the current pixel. The “least central variance direction” is then determined by finding the direction which has minimal “1-D central variance”. Then, the current pixel is updated by replacing its value with the average value of the three pixels along the “least central variance direction”, to essentially remove undesirable blocking artifacts.
Name / Title
Company / Classification
Phones & Addresses
Peng Yu Lin
GRAND BUFFET OF BOARDMAN, LLC
Peng Lin
LINS PADTHAI LLC
Peng C. Lin President
EXPEEDEE INC
22310 Janice Ave, Cupertino, CA 95014
Peng Lin President
MINDONG LIANYI GROUP AMERICA DAPENG CORP
2530 Corporate Pl STE A111, Monterey Park, CA 91754