Investigations on Adaptive Block Compressive Sensing Techniques for Efficient Image Compression

Abstract

The digital revolution has led to an explosion of data generated by sensors and sensing systems, including images. Managing and processing such vast amounts of data can be challenging due to transmission, storage, and computational requirements. To address this issue, various techniques are explored to efficiently handle and reconstruct data while discarding unnecessary information. Data compression techniques aim to reduce the size of the data, but neglects some relevant information resulting in loss of fine details, texture, and subtle colour variations in the decompressed image newlineCompressed sensing (CS) is a powerful technique for reducing the amount of sensed data. It is not always the most effective solution in certain compression applications as it adopts non-adaptive random projection. The random direction of the projection subspace in conventional compressed sensing can lead to a degradation in overall reconstructed image quality newline