Hybrid Approaches to Image Coding: A Review

Now a days, the digital world is most focused on storage space and speed. With the growing demand for better bandwidth utilization, efficient image data compression techniques have emerged as an important factor for image data transmission and storage. To date, different approaches to image compression have been developed like the classical predictive coding, popular transform coding and vector quantization. Several second generation coding schemes or the segmentation based schemes are also gaining popularity. Practically efficient compression systems based on hybrid coding which combines the advantages of different traditional methods of image coding have also being developed over the years. In this paper, different hybrid approaches to image compression are discussed. Hybrid coding of images, in this context, deals with combining two or more traditional approaches to enhance the individual methods and achieve better quality reconstructed images with higher compression ratio. Literature on hybrid techniques of image coding over the past years is also reviewed. An attempt is made to highlight the neuro-wavelet approach for enhancing coding efficiency.

@article{J2011,
  title     = {Hybrid Approaches to Image Coding: A Review},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {2},
  number    = {7},
  year      = {2011},
  publisher = {The Science and Information Organization},
  author    = {Rehna V J and Jeya Kumar. M. K},
  doi       = {10.14569/IJACSA.2011.020716},
  url       = {https://doi.org/10.14569/IJACSA.2011.020716}
}