Abstract: A method for generating a target perspective model referenced for depth map generation includes at least following steps: receiving a first input image; utilizing a region-based analysis unit for analyzing a plurality of regions in the first input image to extract image characteristics of the regions; and determining the target perspective model according to at least the image characteristics. Another method for generating a target perspective model referenced for depth map generation includes: receiving a first input image; determining a first perspective model in response to the first input image; and utilizing a perspective model generation unit for generating the target perspective model by a weighted sum of the first perspective model and at least one second perspective model.

Abstract: In accordance with at least some embodiments of the present disclosure, a process for converting a two-dimensional (2D) image based on edge information is described. The process may include partitioning the 2D image to generate a plurality of blocks, segmenting the plurality of blocks into a group of regions based on edges determined in the plurality of blocks, assigning depth values to the plurality of blocks based on a depth gradient hypothesis associated with the group of regions, wherein pixels in each of the plurality of blocks are associated with a same depth value, and generating the depth map based on the depth values of the plurality of blocks.

Abstract: A system and method of correcting a depth map for 3D image is disclosed. A spatial spectral transform unit extracts pixels of object boundaries according to an input image, wherein the spatial spectral transform unit adopts Hilbert-Huang transform (HHT). A correction unit corrects an input depth map corresponding to the input image according to the pixels of object boundaries, thereby resulting in an output depth map.

Abstract: In accordance with at least some embodiments of the present disclosure, a process for enhancing a two-dimensional (2D) image is described. The process may include generating a depth map for the 2D image based on edges detected from the 2D image, wherein the depth map can be used to convert the 2D image to a 3D image. The process may further include enhancing the 2D image using the depth map.

Abstract: A method of revising depth of a three-dimensional (3D) image is disclosed. The method comprises the following steps: firstly, at least one initial depth map associated with one image of the 3D image pair based on stereo matching technique is received, wherein the one image comprises a plurality of pixels, and the initial depth map carries an initial depth value of each pixel. Then, the inconsistence among the pixels of the one image of the 3D image pair is detected to estimate a reliable map. Finally, the initial depth value is interpolated according to the reliable map and the proximate pixels, so as to generate a revised depth map by revising the initial depth value.

Abstract: A nonlinear depth remapping method includes the following steps: firstly, an initial depth map associated with at least one image is received, with the image comprising a plurality of pixels and the initial depth map carrying an initial depth value of each pixel. Then, an exponential function is utilized to adjust the initial depth values, so as to generate an adjusted depth map.

Abstract: In a method of block-based motion estimation a motion vector map is obtained by obtaining a motion vector of each macroblock (MB) in the current frame with respect to the reference frame. The motion vector of each MB in an interpolated frame is then determined according to the motion vector map.

Abstract: A method and apparatus of tile-based belief propagation are disclosed. An image is split into a number of tiles. Messages are iteratively generated within each of the tiles based on the messages from neighboring pixels to the tile at a previous iteration, wherein each message represents information of a state of the pixel. The generated messages for sending out of the tiles are stored. Labels are then determined based on the stored messages, wherein each label represents the state of the pixel.

Abstract: A driving support system with plural dimension processing units (DPUs) for indicating a condition of a surrounding area is disclosed. The driving support system of a vehicle includes plural image capturing devices disposed around the vehicle; at least a dimension processing unit (DPU) connected with the plural image capturing devices for receiving images from the plural image capturing devices and then producing plural related depth maps; a controller connected with the DPU for receiving the plural related depth maps and then producing an indicating data; and a display device connected with the controller for displaying the indicating data around the vehicle in a vertical view.

Abstract: The invention presents a system and method for obtaining object depth through digital signal processing. The auto depth-field capturing method for a camera includes the steps of a) taking plural images; b) estimating plural epipolar data of the plural images for obtaining a matrix describing motion and directional vectors; c) estimating a location data in response to the plural epipolar data and the matrix; d) rectifying the plural images corresponding to the plural epipolar data for obtaining plural rectified images; e) calculating the location data for obtaining disparity vectors of the rectified images; f) obtaining a depth map in response to the disparity vectors and the location data; and g) painting a 3D image in correspondence with the depth map. The depth estimation method of the present invention is fully automatic without change of the camera itself.

Abstract: In accordance with at least some embodiments of the present disclosure, a processor for performing stereo matching of a first image and a second image is described. The processor may include a first pipeline stage configured to generate data costs associated with a first tile selected from the first image, wherein the data costs is generated based on pixels in the first tile and corresponding pixels in the second image. The processor may include a second pipeline stage configured to generate disparity values associated with the first tile and an outbound message from the first tile to one of neighboring tiles in the first image, wherein the disparity values and the outbound message are generated based on the data costs and inbound messages from the neighboring tiles to the first tile.

Abstract: A depth-based image enhancement system is disclosed. A depth estimation unit generates three-dimensional (3D) depth information from a two-dimensional (2D) image. Subsequently, an image enhancement unit enhances the 2D image according to the 3D depth information.

Abstract: A system of generating three-dimensional (3D) depth information is disclosed. A color and object independent local blurriness estimation unit analyzes blurriness of each pixel of a two-dimensional (2D) image. Subsequently, a depth assignment unit assigns depth information to the 2D image according to the analyzed blurriness.

Abstract: In a method of occlusion handling, a reference frame and a current frame are first provided, and at least one foreground object is determined. At least a covered region or an uncovered region with respect to the foreground object is determined. The covered region is then interpolated exclusively accordingly to the current frame, or the uncovered region is interpolated exclusively according to the reference frame.

Abstract: In a method of block-based motion estimation a motion vector map is obtained by obtaining a motion vector of each macroblock (MB) in the current frame with respect to the reference frame. The motion vector of each MB in an interpolated frame is then determined according to the motion vector map.

Abstract: A content-adaptive overdrive system and method, for a display panel, include a frame difference device and an overdrive device. The frame difference device generates a frame difference map according to a current frame and a previous frame. The frame difference map includes a number of flags respectively indicating similarity between corresponding pixels or blocks of the current frame and the previous frame. The overdrive device adaptively performs an overdrive function based on the frame difference map, the current frame, the previous frame and an overdrive lookup table, hence resulting in an overdrived frame.

Abstract: In accordance with at least some embodiments of the present disclosure, a process for generating a depth map for converting a two-dimensional (2D) image to a three-dimensional (3D) image is described. The process may include generating a depth gradient map from the 2D image, wherein the depth gradient map is configured to associate one or more edge counts with one or more depth values, extracting an image component from the 2D image, wherein the image component is associated with a color component in a color space, determining a set of gains to adjust the depth gradient map based on the image component, and generating the depth map by performing depth fusion based on the depth gradient map and the set of gains.

Abstract: A method and apparatus of tile-based belief propagation are disclosed. An image is split into a number of tiles. Messages are iteratively generated within each of the tiles based on the messages from neighboring pixels to the tile at a previous iteration, wherein each message represents information of a state of the pixel. The generated messages for sending out of the tiles are stored. Labels are then determined based on the stored messages, wherein each label represents the state of the pixel.

Abstract: A system and method of generating three-dimensional (3D) depth information is disclosed. The vanishing point of a two-dimensional (2D) input image is detected based on vanishing lines. The 2D image is classified and segmented into structures based on detected edges. The classified structures are then respectively assigned depth information.

Abstract: A system and method of generating three-dimensional (3D) depth information is disclosed. A classification and segmentation unit segments a two-dimensional (2D) image into a number of segments, such that pixels having similar characteristics are classified into the same segment. A spatial-domain texel density analysis unit performs texel density analysis on the 2D image to obtain textual density. A depth assignment unit assigns depth information to the 2D image according to the analyzed textual density.