Abstract
The main objective of image compression is to diminish the number of bits required to represent an image by eliminating the spatial and spectral redundancies. Image compression is classified as lossy and lossless compression. Lossy compression reduces the size of a file by removing redundant information. Whereas, in the lossless compression there won't be any loss of information upon the extraction of original image from the compressed image. The aim of this paper is to do a comparison between two latest works in the image compression namely, An Efficient DCT-Based Image Compression System Based on Laplacian Transparent Composite Model and An Innovative Lossless Compression Method for Discrete-Color Images. From the analysis, it is observed that on average, An Efficient DCT-Based Image Compression System Based on Laplacian Transparent Composite Model reduces the compression rate by 25% in the case of images, compared to JBIG2. It is also observed that this approach is better suited for traditional images like Lena and Goldhill while An Innovative Lossless Compression Method for Discrete-Color Images is better suited for charts and maps.
Sign-in/Register to access full text options 
Free) 
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
