IMAGE COMPRESSION USING DISCRETE TCHEBICHEF TRANSFORM AND SINGULAR VALUE DECOMPOSITION (DTT-SVD)

Main Article Content

S. Elamparuthi, N. Puviarasan

Abstract

Nowadays, images are sent through the internet in very large scale. More memory space and transmission bandwidth are needed for an uncompressed image. So, it increases the size of the image database. By greatly reducing the need for bit-rate by using the redundancies that are usually present in video and image signals, compression can be accomplished. The device that achieves a high degree of compression while retaining information relevant to the sensitive pictures is necessary. The DTT will replace the DCT. The new high-energy compaction and lower transformation of computational benefit used for compression are DTT. A given matrix is divided into a product of orthonormal matrices and a diagonal matrix by the SVD technique. Combining the DTT and SVD strategies speeds up the transition of the image into a non-visual format intended to minimise inter-pixel redundancy, and without compromising efficiency, the SVD will delete enormous portions of our matrix. DTT-SVD compression has been shown to result in higher CR, PSNR values ranging from 28 to 32db, and lower MSE values compared to the DCT and SVD form combine (DCT-SVD).

Article Details

Section
Articles