Design of Multiplier for Medical Image Compression Using Urdhava Tiryakbhyam Sutra

Abstract

Compressing the medical images is one of the challenging areas in healthcare industry which calls for an effective design of the compression algorithms. The conventional compression algorithms used on medical images doesn’t offer enhanced computational capabilities with respect to faster processing speed and is more dependent on hardware resources. The present paper has identified the potential usage of Vedic mathematics in the form of Urdhava Tiryakbhyam sutra, which can be used for designing an efficient multiplier that can be used for enhancing the capabilities of the existing processor to generate enhance compression experience. The design of the proposed system is discussed with respect to 5 significant algorithms and the outcome of the proposed study was testified with heterogeneous samples of medical image to find that proposed system offers approximately 57% of the reduction in size without any significant loss of data.

Significant medical image compression techniques: a review

“…Studies [17], [22], [26], [33], [37] and [38] used the Huffman method whose algorithms are characterised by dynamism of computing and searching for duplicates. It is used as the last step in the compression process after a series of processors to be used efficiently.…”

“…Time is one of the most significant problems facing these algorithms due to their use of the laws of probability for the occurrence of each element in the image. Studies [6], [13] and [37] used RLE algorithms, which are distinguished by great effectiveness in processing text and images compared to audio data. This method is considered a lossless type and is good when the image is grey.…”

“…Suma and Sridhar [37] proposed the Huffman compression system based on the Urdhava Tiryakbhyam approach, which performs vertical and crossover multiplication and removes the excess data without distorting the image. This system leads to higher power consumption required for compressing grey and colour medical images by minimising the frequency of the clock.…”

“…Finally, the binary mask is compressed using the RLE method. Suma and Sridhar [37] used the RLE technique in addition to the Huffman technique. Kulkarni et al [13] used the RLE technique in addition to transformation techniques.…”

Functional Verification of Large-integers Circuits using a Cosimulation-based Approach

“…Hardware-based implementations of such algorithms have proved to be more efficient than equivalent software's programs in terms of speed and resources usage. This is mainly due to exploring new design architectures [7][8][9][10][11][12]. Such designs are generally written in hardware description languages (HDLs).…”