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 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 device includes an image processing unit, an over-driving unit, and an up-sampler. The image processing unit receives a full-resolution 3D input image and outputs a half-resolution 3D image to a memory. The over-driving unit is coupled to the image processing unit and the memory for over-driving a current half-resolution 3D image outputted from the image processing unit according to a previous half-resolution 3D image stored in the memory. The up-sampler is selectively coupled to the over-driving unit for up-sampling an over-driven half-resolution 3D image outputted from the over-driving unit to output a full-resolution 3D output image.
Abstract:
A method of detecting image format includes dividing a single-frame image into a plurality of macro-blocks; calculating a correlation coefficient of a left-half image of the single-frame image and a right-half image of the single-frame image as a first global similarity; calculating a correlation coefficient of a top-half image of the single-frame image and a bottom-half image of the single-frame image as a second global similarity; calculating a portion difference of each macro-block; comparing the portion differences of the left-half image and the right-half image, for acquiring a first local similarity; comparing the portion differences of the top-half image and the bottom-half image, for acquiring a second local similarity; and detecting an image format of the single-frame image according to the first global similarity, the second global similarity, the first local similarity, the second local similarity, a first threshold and a second threshold.
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.