@article{Breesam_Zalzala_Najjar_2024, title={Walsh Transform-based Image Compression for Less Memory Usage and High Speed Transfer}, volume={18}, url={https://oiccpress.com/Majlesi-Journal-of-Electrical-Engineering/article/walsh-transform-based-image-compression-for-less-memory-usage-and-high-speed-transfer/}, DOI={10.30486/mjee.2023.1996722.1267}, abstractNote={The rising use of digital imaging applications has recently boosted the demand for different image compressing algorithms. Picture compression is used to reduce unnecessary information from an image. We can store the vital information of a picture via image compression, reducing storage space, time, and transmission bandwidth. Although the results of lossy compression reconstruction are not similar to the original image the compression technique is essential to save a large amount of memory and increase the speed of transmission, especially when dealing with images. In this research a database of different five images was considered namely; woman, car, Lenna, peppers, and house with sizes of 33, 47, 40, 44, and 51 Kb respectively. The compression was fulfilled by Walsh transform with four compression ratios 5%, 10%, 15%, and 20%. The Walsh transform performed well and gave the highest average PSNR of 29.1904 during a 10% of compression ratio.  }, number={1}, journal={Majlesi Journal of Electrical Engineering}, publisher={OICC Press}, author={Breesam, Aqeel Majeed and Zalzala, Ali M. and Najjar, Esraa}, year={2024}, month={Apr.}, keywords={Walsh Hadamard Transform (WHT), Image Compression, Peak signal-to-noise ratio (PSNR), Mean Square Error (MSE), Database Image} }