Fast codebook design method for image vector quantisation

作     者：Fan, Hang-Yu Lu, Zhe-Ming 

作者机构：Zhejiang Univ Sch Aeronaut & Astronaut Hangzhou 310027 Zhejiang Peoples R China 

出 版 物：《IET IMAGE PROCESSING》 (IET影像处理)

年 卷 期：2018年第12卷第12期

页      面：2311-2318页

核心收录：

学科分类：0808[工学-电气工程] 1002[医学-临床医学] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：vector quantisation particle swarm optimisation data compression image coding pattern clustering PSO algorithm pooled images PSO process original images reverse cast process computation time pooling window codebook quality hybrid method fast codebook design method image vector quantisation data compression image VQ general particle swarm optimisation clustering method 

摘      要：Vector quantisation (VQ) is a widely used method for data compression or data clustering. This study proposes a fast codebook design method for image VQ. General particle swarm optimisation (PSO)-K-means hybrid methods for codebook design take too much time. To deal with this problem, the authors present a new clustering method, which takes a very short time and generates a pretty good codebook. This method contains four parts, i.e. pooling, PSO algorithm, reverse cast, and K-means algorithm. Pooled images are used for the PSO process while original images are used for K-means fine-tuning, and these two processes connected by the reverse cast process. In the authors experiment, this method can dramatically reduce the computation time by using big sizes of pooling window or enhance the codebook quality by using small sizes of pooling window. They can make the calculation time almost one-tenth of that of the PSO-K-means hybrid method, and the scheme is also faster than the K-means algorithm. Experimental results demonstrate that the main advantages of the proposed algorithm lie in the fact that it can reduce the computation time and enhance the quality of codebooks.