Lossy to Lossless Image Coding Using Quad Tree Based Partitioning

Abstract

Lossy to Lossless Image Coding is a compression technique used for compressing the images by removing redundant information between different resolutions from the image. Lossless image compression can be achieved by using Integer Wavelet Transform, because of its Multi resolution nature and it does not contain floating point coefficients. In this paper we proposed a new method called QTBP (Quad Tree Based Partitioning), for lossy to lossless image compression, it can also be useful in low complexity coding process. This method is based on block quantization and we used sets of type S for partitioning process. There are various progressive transmission methods are available in the literature. The disadvantage of JPEG2000 is compression ratios are less and the disadvantages of SPIHT are complexity increases in finding the parent child relations with the increased decomposition levels, and SPIHT doesn’t consider the energy concentration in the same level. QTBP overcomes the disadvantages of JPEG2000 and SPIHT. This method has very less complexity and it considers energy concentration in the same level when compared to the existing methods. In this paper, basic concepts and algorithm of QTBP is discussed. It is found that the method QTBP give better results than the state of the art methods like JPEG 2000 and SPIHT.