An Image Compression Algorithm and Its Analysis on the Basis of Different Masking Tables

Abstract

Image compression algorithms are used to reduce the redundancies in the representation of the data so that the data storage requirements and the communication cost can be reduced. Different algorithms have been developed to reduce the size of an image like JPEG, PNG, SPIHT, etc. In this paper, we mainly focus on the JPEG image compression algorithm because it is mostly used in the Internet and Multimedia based applications. In JPEG, quantization tables and masking tables are used as the main source for the compression of the data. Based on our review, we identify that in literature less attention is given to analyze the effect of the masking tables during the implementation of the JPEG algorithms. Therefore, to address this research issue, in this paper, we analyze the effect of the masking tables used during the JPEG image compression algorithms.