Curvelet Based Efficient Image Compression Technique by Spiht with PSO

In recent years, Curvelet Transform is the most preferred technique for image compression. It is proposed that an efficient and fast image compression scheme based on all level curvelet coefficients with SPIHT (Set Partitioning in Hierarchical Trees).After many passes of coding with SPIHT, it degrades the coding performance.There was a need of a transform that handles two dimensional singularities along the curves sparsely. This gives the origin of new multi-resolution curvelet transform. The designed curvelet techniques are used to represent the edges and to handle two dimensional singularities along curves sparsely. Now the selected all level curvelet coefficients information is applied with SPIHT encoding. Then this output is stored as a bit stream.In addition, PSO (Particle Swarm Optimization) helps to reasonably allocate bits between source coding and channel coding across bit streams.Then SPIHT decoding has been applied and inverse curvelet transform has been taken to reconstruct the image. Different images with different sizes have been tested in the experiment and the results are listed.