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Probabilistic Decision Logic based Image Coding for Biomedical Image Compression


Abdul Khader Jilani Saudagar


Vol. 20  No. 7  pp. 61-69


The domain of biomedical image processing has developed with various coding approaches, and novel techniques which are running from basic compression models to top notch applications. The improvement in this domain has given birth to novel methods for coding with images using Artificial Intelligence techniques which can be easily integrated with real-time clinical systems. In the field of medicine, clinical findings have all time remained a problem for precise treatment especially if the patient is in the remote location. To overcome this problem, automated systems were developed. These automated systems needs transmission of medical images at variable bit rates which is one of the major limitation the hospitals are struggling with. To overcome this problem the proposed work objective is to develop a new algorithm to maintain reduced processing overhead and transmit images over variable bit rate. However images are to be processed with optimal learning rule so that the complexity in coding should be reduced and transmission is made easy. With this objective, probabilistic decision logic for image coding is proposed. Various metrics were used to compare the results obtained using the proposed approach with JPEG image compression standard. The proposed approach has improved results in comparison to other traditional coding systems.


Fuzzy logic, Image compression, Medical image processing, Probabilistic decision logic.