Sajid Ullah Khan*, Najeeb Ullah, Imran Ahmed, Wang Yin Chai and Shahid Ullah Pages 845 - 852 ( 8 )
Background: The area of image processing extends from basic image compression model to high end applications such as astronomical data processing and medical image processing. Images have vast features and coding them into lower bit rates results in the loss of information.
Methods: This study proposes a novel hybrid approach to compress the image no loss of information and to maintain reduced processing overhead.
Discussion: To validate the proposed approach, the suggested method is tested on different medical samples and the obtained results are compared with results retrived through the conventional JPEG based coding approach.
Conclusion: The experimental results show that the proposed approach performs efficiently and can be implemented in realworld applications.
Image compression, coefficients learning, learning based coding, probabilistic decision algorithm, hybrid approach, JPEG.
FCSIT, Universiti Malaysia Sarawak, Sarawak, CECOS University of IT and Emerging Sciences, Peshawar, Institute of Management Sciences, Peshawar, FCSIT, Universiti Malaysia Sarawak, Sarawak, FCSIT, Universiti Malaysia Sarawak, Sarawak