Adaptive Lossy Color Image Compression System Based on Hybrid Algorithm (Baghdad Science Journal, 2024)
As the digital age progresses, multimedia technologies have become commonplace, with users expecting high-quality audio, video, and image content across various platforms and devices.  As a result, the quantity of data produced by these multimedia programs has grown substantially. Also, the explosive growth in the use of multimedia has led to a rise in the quantity of images that are used and created, which creates challenges, in relation to the requirement for increased storage capacity and enhanced data transport speed. To address these challenges, image compression has emerged as a critical solution by decreasing the volume of the image without significantly degrading their quality. As technology advances further, the need for more image compression techniques will become more important. This paper presents a hybrid lossy image compression system by using four compression techniques which are Bit plane slicing, Discrete wavelet transform (DWT), Discrete cosine transform (DCT), and Arithmetic coding. To implement this proposed method three experiments were performed by using images of varying dimensions, namely (256 * 256), (512 * 512), and (1024 * 1024) and four different quantization coefficients. For efficiency performance measurement of the proposed system, three metrics were used: Peak signal-to-noise ratio (PSNR), Structural similarity index (SSIM), and compression ratio (CR). The results showed that the proposed hybrid system was successful in raising the compression ratio in comparison with standard JPEG as the CR when using jpeg reached 35%, while the suggested system provided a higher CR of 62% with keeping a satisfactory level of image quality.