Biomedical image compression using fuzzy transform and deterministic binary compressive sensing matrix

Bio medical images are very important in analysing the internal structure of the body in a non-invasive method, to diagnose for any abnormalities and provide proper treatment to the patients. Medical images include X-rays, CT scan and MRI scan etc. It is necessary to compress these images, so that they can be easily stored and communicated from one place to another. The result of compression should be in such a way that, quality of the compressed image should be good and the compression ratio should be high. The biomedical images are mainly prone to impulse noise which may lead to degradation of image quality. So it is important to filter the impulse noise from the biomedical images without affecting the details of the image. In this paper the filtering of impulse noise from the biomedical images is done using fuzzy transform, followed by compressive sensing to compress the bio medical images without losing information content. Compressive sensing uses a sensing matrix to measure random samples from the image signal. This paper proposes the compression of biomedical images using a deterministic binary compressive sensing matrix and for the recovery of the biomedical image, Orthogonal Matching Pursuit (OMP) is used.

Automated summary

Biomedical images are crucial for diagnosis and treatment, and compression and filtering techniques can improve image quality and reduce the complexity of data transmission.