45 results about "Texture coding" patented technology

Methods of adaptive transform type based on transform unit (TU) size for enhancement layer (EL) coding and multiple motion candidates for EL coding based on corresponding base layer (BL) video data are provided. One method selects a transform type from multiple allowable transform types based on the TU size and applies the selected transform type to the transform units of the inter-layer prediction processed data. Another method derives multiple motion candidates for the EL video data coded in Merge mode or Inter mode based on motion information associated with the corresponding BL video data.

An apparatus and method is provided for highly scalable intraframe video coding. The conventional macroblock DCT tools are integrated with the subband filter banks for the improved efficiency of scalable compression. The enhancement layers are represented in a subband domain and coded by an inter-layer frame texture coder utilizing inter-layer prediction signal formed by the decoded previous layer. Each quality enhancement layer is additionally scalable in resolution.

A motion estimation method using adaptive mode decision is disclosed. The method includes a motion vector difference value calculation step of calculating a motion vector difference value using an input motion vector estimation value x component for a current block and an input x offset corresponding to a current SAD. At the MVD Variable Length Coding (VLC) step, the length of a bit string, which is obtained by performing variable-length coding on an MVDx, is calculated. At a motion vector difference value calculation step, a motion vector difference value is calculated using an input motion vector estimation value y component for a current block and an input y offset corresponding to the current SAD. At an MVD VLC step, the length of a bit string, which is obtained by performing variable-length coding on an MVDy, is calculated. Thereafter, the amount of motion vector coding is produced by adding the MVDx and the MVDy. The amount of texture coding of a current block or a macro block is estimated using SAD values and quantization coefficients of previous macro blocks. A SAD correction coefficient is produced using the amount of motion vector coding and the texture vector coding amount. Finally, the SAD values are multiplied by the SAD correction coefficient, thus correcting the SAD values.

Methods of adaptive transform type based on transform unit (TU) size for enhancement layer (EL) coding and multiple motion candidates for EL coding based on corresponding base layer (BL) video data are provided. One method selects a transform type from multiple allowable transform types based on the TU size and applies the selected transform type to the transform units of the inter-layer prediction processed data. Another method derives multiple motion candidates for the EL video data coded in Merge mode or Inter mode based on motion information associated with the corresponding BL video data.

A texture encoding apparatus includes a texture data acquisition unit configured to acquire texture data of a texture set provided under a plurality of different conditions, a block segmentation unit configured to segment the texture data into a plurality of block data items each of which contains a plurality of pixel data items whose values corresponding to the conditions fall within a first range and whose pixel positions fall within a second range in the texture set, a block data encoding unit configured to encode each of the block data items to produce a plurality of encoded block data items, and a block data concatenation unit configured to concatenate the encoded block data items to generate an encoded data item of the texture set.

The invention discloses a three-dimensional reconstruction method based on texture-coded images, which includes: step 1, projecting a color-coded image generated by M-array coding onto an object to be measured, and using a camera to photograph the region to be measured to obtain left and right images. In step 2, the target area is extracted based on the Hough circle detection method and the principle of perspective transformation, so as to avoid the influence of environmental debris on the projection area. Step 3, image enhancement based on color migration technology and color recognition preprocessing, converting the color information of the image into code values. Step 4, direct decoding for M-array encoding method to obtain matching point pairs. Step 5, using the obtained point pairs with the same name, perform 3D reconstruction based on the principle of stereo vision, and obtain the 3D coordinates of the spatial points corresponding to the 2D points. The present invention combines spatial codec and binocular vision structured light three-dimensional reconstruction technology to improve the speed and accuracy of three-dimensional reconstruction, and provides a new idea for high-efficiency three-dimensional reconstruction under the premise of maintaining a high degree of simulation.

The invention discloses an image processing method for encoding pulse sequences, which encodes multi-level information on images, and encodes information on different levels of the images into pulse sequences according to the time sequence; including: converting the image into a grayscale image and converting the image Standardize the gray value of the gray image; encode the shape, feature points, color, and texture of the gray image into pulses; then arrange the encoded pulses in a set order to form a series of pulse sequences. The invention effectively utilizes the information of various levels carried by the image, and reduces non-key information at the same time. For the spiking neural network, the information completeness of the spiking sequence input by the neural network is improved, the redundancy of information is reduced, and the information processing efficiency of the spiking neural network can be improved. For signal processing, the information capacity of the information source and the coding efficiency of information are improved.

The invention provides a hand vein recognition method based on the fusion of structure coding characteristics and texture coding characteristics, belonging to the technical field of intelligent monitoring in computer vision. The method comprises the following steps of: step 1, acquiring and preprocessing an image; step 2, extracting the structure coding characteristics; step 3, extracting the hand vein texture coding characteristics; step 4, fusing the structure coding characteristics with the hand vein texture coding characteristics; and step 5, performing recognition through a sorter, thereby obtaining a result. The invention provides the hand vein recognition method based on the fusion of the structure coding characteristics and the texture coding characteristics, wherein binary codingis performed on the extracted structure characteristics and texture characteristics, which is advantageous for the retention of information in the characteristic fusion; the result obtained by fusingthe characteristics is far better than the result of recognition obtained by only employing the structure coding characteristics and the result of recognition obtained by only employing the texture coding characteristics; and the robustness for image distortion and wrong segmentation is high, therefore, the hand vein can be correctly recognized in the presence of certain image distortion and wrong segmentation.