In this paper, a new and fast-searching algorithm for vector quantization is presented. Two inequalities, one used for terminating the searching process and the other used to delete impossible codewords, are presented to reduce the distortion computations. Our algorithm makes use of a vector's features (mean value, edge strength, and texture strength) to reject many unlikely codewords that cannot be rejected by other available approaches. Experimental results show that our algorithm is superior to other algorithms in terms of computing time and the number of distortion calculations. Compared with available approaches, our method can reduce the computing time and the number of distortion computations significantly. Compared with the best method of reducing distortion computation, our algorithm can further reduce the number of distortion calculations by 29% to 58.4%. Compared with the best encoding algorithm for vector quantization, our approach also further reduces the computing time by 8% to 47.7%.

Fast-searching algorithm for vector quantization using projection and triangular inequality

An efficient nearest neighbor codeword search algorithm based on Hadamard transform for vector quantization is presented in This work. Four efficient elimination criteria are derived from two important inequalities based on three characteristic values in the Hadamard transform domain. Before the encoding process, all codewords in the codebook are Hadamard-transformed and sorted in the ascending order of their first elements. During the encoding process, we firstly perform the transform on the input vector and calculate its characteristic values, and initialize the current closest codeword of the input vector to be the codeword whose first element of Hadamard transform is nearest to that of the input vector, and secondly use the proposed elimination criteria to find the nearest codeword to the input vector using the up-down search mechanism near the initial best-match codeword. Experimental results demonstrate the proposed algorithm is much more efficient than most existing nearest neighbor codeword search algorithms in the case of high dimension.

Hadamard transform based fast codeword search algorithm for high-dimensional VQ encoding

High Efficiency Video Coding achieves twofold coding efficiency improvement compared with its predecessor H.264/MPEG-4 Advanced Video Coding. However, it suffers from high computational complexity due to its quad-tree structure in motion estimation (ME). This paper exposes the use of depth maps in the multiview video plus depth format for relieving the computational burden. The depth map provides an intimation of the objects’ distance from the projected screen in a 3D scene, which is explored in adaptive search range determination in this paper. The proposed algorithm exploits the high temporal correlation between the depth map and the motion in texture. By utilizing this correlation, a depth/motion relationship map is built for a mapping process. For each block, this forms a tailor-made search range with a motion-aware asymmetric shape to skip unnecessary search points in ME. The obtained search range can be further adjusted by taking the influence of 3D-to-2D projection into consideration. Simulation results reveal that, compared to the full search approach, the proposed algorithm can reduce the complexity by 93% on average, whereas the coding efficiency can be maintained. Besides, the proposed search range determination can work well with other fast search ME algorithms in the literature.

Adaptive Search Range for HEVC Motion Estimation Based on Depth Information

The fractal image compression is a recent tool for encoding natural images. It builds on the local self-similarities and the generation of copies of blocks based on mathematical transformations. Th...

An improved fractal image compression using wolf pack algorithm

The Intra Block Copy (IntraBC) mode is a very efficient coding tool for the screen content coding (SCC) extension in High Efficiency Video Coding (HEVC) by finding the repeating patterns within the same frame. Yet, it also brings along impractically high computational complexity for SCC, which can be a double of the conventional HEVC, as exhaustive block matching is done within the same frame even though there are already some constraints applied to the IntraBC mode. To reduce the complexity, we propose to skip the unnecessary IntraBC mode checking based on the activity and gradient within the coding unit (CU). With our proposed methods, the increased encoding time compared with the conventional HEVC is reduced from 90.0% to 62.2% on average while the coding efficiency can still be maintained with only negligible bitrate increased.

Fast HEVC screen content coding by skipping unnecessary checking of intra block copy mode based on CU activity and gradient

The encoding of vector quantization (VQ) needs expensive computation for searching the closet codeword to the input vectors. In order to reduce computational burden, many researchers have developed some efficient full-search-equivalent algorithm by using the characteristics of the means and variances of a vector. However, some computational redundancies still exist in them. In this paper, we introduce a technique to efficiently partition a vector into two dynamic subvectors according to the patterns inside the block (or vector) and then further improve the computational load. Experimental results show that the proposed method provides a higher codeword searching efficiency than other existing algorithms.

A fast encoding algorithm for vector quantization

New adaptive partial distortion search algorithm for block motion estimation

The major drawback of the fractal image compression is the high encoding complexity to find the best match between a range block and a large pool of domain blocks. This paper presents a fast fractal-encoding algorithm based on the law of cosines. The number of domain blocks searched to find the best match for each range block is safely reduced by eliminating the ineligible domain blocks using the law of cosines. Simulation results show that the proposed algorithm can produce a completely identical fractal code to that of the exhaustive search in reduced time.

Chou-Chen Wang

Papers

A fast encoding algorithm for vector quantization

New adaptive partial distortion search algorithm for block motion estimation

A fast encoding algorithm for fractal image compression