Abstract

This paper presented comprehensive study with performance analysis of very recent Wavelet transform based image compression techniques. Image compression is one of the necessities for such communication. The goals of image compression are to minimize the storage requirement and communication bandwidth. Compression is achieved by the removal of redundant data. Discrete Wavelet Transform (DWT) is a recently developed compression technique in image compression. DWT image compression includes decomposition (transform of image), Detail coefficients thresholding, and entropy encoding. This paper mainly describes the transform of an image using DWT and thresholding techniques. In this paper we have taken the standard image Lena of size 256X256 of 8 bit depth and applied DWT (haar). Then two results set are obtained by applying two different techniques of thresholding and then compare the result.Keywords: Discrete Cosine Transform, Wavelet Transform, JPEG Compression and Entropy Encoding

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.