A FAST CODEBOOK DESIGN ALGORITHM BASED ON A FUZZY CLUSTERING METHODOLOGY
Ahmed Abdelwahab, NORA S. MUHARRAM
Abstract
Ahmed Abdelwahab, NORA S. MUHARRAM
Abstract
In this paper, a new fast one-step codebook design algorithm for vector quantization is proposed for image coding. The algorithm utilizes a fuzzy clustering methodology for best clustering of data vectors in the training space. The codebook design process terminates in just one step so that it is highly computationally efficient as compared to other reported algorithms. To improve the coding efficiency, image blocks are further classified into two classes and a different codebook is designed for each class. The two codebooks are augmented to form one codebook so that there is no need to send class information. Moreover, entropy coding is used to send codevector index to the receiver for further bit rate reduction. Simulation results are presented to show the superior performance of the proposed algorithm in terms of PSNR as compared to the state-of-the-art codebook design algorithms.
OpenAlex reports 18 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
In this paper, a new fast one-step codebook design algorithm for vector quantization is proposed for image coding. The algorithm utilizes a fuzzy clustering methodology for best clustering of data vectors in the training space. The codebook design process terminates in just one step so that it is highly computationally efficient as compared to other reported algorithms. To improve the coding efficiency, image blocks are further classified into two classes and a different codebook is designed for each class. The two codebooks are augmented to form one codebook so that there is no need to send class information. Moreover, entropy coding is used to send codevector index to the receiver for further bit rate reduction. Simulation results are presented to show the superior performance of the proposed algorithm in terms of PSNR as compared to the state-of-the-art codebook design algorithms.
Key concepts: Codebook, Linde–Buzo–Gray algorithm, Vector quantization, Cluster analysis, Algorithm, Computer science, Coding (social sciences), Image compression