Image Compression Using Hybrid Combinations of DCT SVD and RLE

Image Compression finds a significant place in the field of research. In this paper we are proposing a scheme for hybrid image compression which uses Discrete Cosine Transform, Singular Value Decomposition and Run length Encoding. Discrete Cosine Transform is applied to the image. Then DCCoefficient is taken out from Discrete Cosine Transformed Matrix and stored or transmitted separately. The Discrete Cosine Transformed matrix without DC-coefficient is truncated with a threshold value. To this truncated matrix Singular Value Decomposition is applied. The matrices obtained from the Singular Value Decomposition are again truncated with suitable threshold value. Then these matrices are multiplied back.The resultant matrix is again truncated with threshold value. Then this matrix is quantized. The quantized matrix is converted into sparse matrix form. Then sparse matrix elements under goes data type conversion.The column elements of the sparse matrix are run length encoded and then compressed form of the image can be obtained. This compressed form can be stored or transmitted. An effort is also made to compare the number of memory bytes obtained in this method with the three other methods which are discussed. Keywords-- DCT-Discrete Cosine Transform, SVD-Singular Value Decomposition, MSE-Mean Squared Error, PSNR-Peak Signal to Noise Ratio, CR-Compression Ratio ,RLE-Run Length Encoding