This paper presents a novel wavelet compression technique to increase compression of images. Based on zerotree entropy coding method, this technique initially uses only two symbols (significant and zerotree) to compress image data for each level. Additionally, sign bit is used for newly significant coefficients to indicate them being positive or negative. Contrary to isolated zero symbols used in conventional zerotree algorithms, the proposed algorithm changes them to significant coefficients and saves its location, they are then treated just like other significant coefficients. This is done to decrease number of symbols and hence, decrease number of bits to represent the symbols used. In the end, algorithm indicates isolated zero coordinates that are used to change the value back to original during reconstruction. Noticeably high compression ratio is achieved for most of the images, without changing image quality.

Wavelet based image compression is getting popular due to its promising compaction properties at low bitrate. Zerotree wavelet image coding scheme efficiently exploits multi-level redundancy present in transformed data to minimize coding bits. In this paper, a new technique is proposed to achieve high compression by adding new zerotree and significant symbols to original EZW coder. Contrary to four symbols present in basic EZW scheme, the modified algorithm uses eight symbols to generate fewer bits for a given data. Subordinate pass of EZW is eliminated and replaced with fixed residual value transmission for easy implementation. This modification simplifies the coding technique as well and speeds up the process, retaining the property of embeddedness.

The rapid growth of multimedia applications has increased interest in the compression of video data. This paper presents a new method for improving the compression ratio of video data, which can be easily used in a multilayer environment for error resilience applications as well. Data of four luminance blocks in a macroblock are processed and arranged in such a way that important macroblock data is compressed in one block(A), while the rest of the three remaining data blocks(H,V,D) are given difference values in the horizontal, vertical and diagonal directions. This results in a reduced bitstream size because of the low-valued data present in the three blocks(H,V,D), giving better compression at low bitrates. In an error resilient environment, the important data block in a macroblock is transmitted in a secure channel while the remaining three blocks with difference data are sent via a lossy channel. If error occurs in the lossy channel, picture can still be reconstructed with reasonably good quality using only the block data that is transmitted in the secure channel.