Abstract:
An image interpolation method is utilized for performing an interpolation on a source image to obtain a destination image. The image interpolation method includes performing a domain transformation on a plurality of pixels of the source image to generate a plurality of first coefficients and a plurality of second coefficients; respectively determining an data interrelationship degree in at least one direction of each first coefficient to generate a plurality of direction results; performing a first interpolation process on the plurality of first coefficients according to the plurality of direction results to generate a plurality of first destination coefficients; performing a second interpolation process on the plurality of second coefficients to generate a plurality of second destination coefficients; performing a reverse domain transformation on the plurality of first destination coefficients and the plurality of second destination coefficients to obtain the destination image.
Abstract:
An image processing method and an image processing apparatus that utilize scrolling text information and moving edge-pairs of an edge map to determine text regions in interpolated frame is introduced herein. Text blocks are detected according to the moving edges-pair of the edge map. Next, a first moving vector histogram and a second moving vector histogram are built according to the detected text blocks. An existence of scrolling text and motion vector of the scrolling text in the frames are determined according to the first and second moving vector histograms. A scrolling text region in at least one of the first frame and the second frame is determined in block line unit, and positions of each scrolling text pixels in an interpolated are determined according to the motion vector of the scrolling text and the scrolling text region in the at least one of the first frame and the second frame.
Abstract:
An image processing apparatus and an image fine-tuning method are provided. The image processing apparatus includes a high-pass filter, a block comparator, an image data reconstructor, and a calculator. The high-pass filter receives a first image to generate a filtered image. The block comparator receives an input image and the first image to generate a block comparison result. The image data reconstructor receives the filtered image and the block comparison result to generate image reconstruction data. The calculator receives the input image and the image reconstruction data to generate an output image.
Abstract:
A three-dimension (3D) image processing method is disclosed. A plurality of asymmetric filtering is performed on an input depth map to obtain a plurality of asymmetric filtering results. One among the asymmetric filtering results is selected as an output depth map. A two-dimension (2D) image is converted into a 3D image according to the output depth map.
Abstract:
Method for detecting disappearance of a pattern is used to detect whether a fixed-still pattern in dynamic displayed images disappears. Method includes analyzing a pattern characteristic parameter which represents the fixed-still pattern from each of images continuously displayed in a time sequence, It is checked whether the pattern characteristic parameter fast decreases from at least greater than a high level to at least less than a low level, as a first state transition. Sum of absolute difference (SAD) values for all of the pixels between a previous image and a current image is calculated. It is checked whether the sum of the SAD values fast increases from at least less than a low level to at least greater than a high level, as a second state transition. When the first state transition and the second state transition occur simultaneously, it is determined that the fixed-still pattern disappears in the display.
Abstract:
An image processing apparatus and an image fine-tuning method are provided. The image processing apparatus includes a high-pass filter, a block comparator, an image data reconstructor, and a calculator. The high-pass filter receives a first image to generate a filtered image. The block comparator receives an input image and the first image to generate a block comparison result. The image data reconstructor receives the filtered image and the block comparison result to generate image reconstruction data. The calculator receives the input image and the image reconstruction data to generate an output image.
Abstract:
A three-dimension (3D) image processing method is disclosed. A plurality of asymmetric filtering is performed on an input depth map to obtain a plurality of asymmetric filtering results. One among the asymmetric filtering results is selected as an output depth map. A two-dimension (2D) image is converted into a 3D image according to the output depth map.
Abstract:
An image processing method and an image processing apparatus that utilize scrolling text information and moving edge-pairs of an edge map to determine text regions in interpolated frame is introduced herein. Text blocks are detected according to the moving edges-pair of the edge map. Next, a first moving vector histogram and a second moving vector histogram are built according to the detected text blocks. An existence of scrolling text and motion vector of the scrolling text in the frames are determined according to the first and second moving vector histograms. A scrolling text region in at least one of the first frame and the second frame is determined in block line unit, and positions of each scrolling text pixels in an interpolated are determined according to the motion vector of the scrolling text and the scrolling text region in the at least one of the first frame and the second frame.
Abstract:
An frame rate up-conversion (FRC) apparatus and method are provided. The motion vector generating circuit compares a previous original frame with a current original frame to obtain the first motion vectors of the blocks of the current original frame, and compares the current original frame and a posterior original frame to obtain the second motion vectors of the blocks of the current original frame. The motion vector correction circuit checks whether the blocks of the second original frame are located in an occlusion area, and corrects the motion vectors of the blocks in the occlusion area based on the first motion vectors and the second motion vectors of the first original frame, the second original frame and the third original frame. The interpolation frame generating circuit creates at least one interpolation frame between the first original frame and the second original frame based on the corrected motion vectors.
Abstract:
Method for detecting disappearance of a pattern is used to detect whether a fixed-still pattern in dynamic displayed images disappears. Method includes analyzing a pattern characteristic parameter which represents the fixed-still pattern from each of images continuously displayed in a time sequence, It is checked whether the pattern characteristic parameter fast decreases from at least greater than a high level to at least less than a low level, as a first state transition. Sum of absolute difference (SAD) values for all of the pixels between a previous image and a current image is calculated. It is checked whether the sum of the SAD values fast increases from at least less than a low level to at least greater than a high level, as a second state transition. When the first state transition and the second state transition occur simultaneously, it is determined that the fixed-still pattern disappears in the display.