01990nas a2200289   4500000000100000000000100001008004100002260001200043653003200055653002700087653002700114653002200141100001800163700002000181700002600201700001900227700001500246700001600261700002600277700002400303245010700327856007900434300001000513490000600523520115700529022001401686       2022                            d  c12/202210aStructural Similarity Index10aFast Fourier Transform10aIntelligent Water Drop10aImage Compression1 aSurinder Kaur1 aGopal Chaudhary1 aJavalkar Dinesh Kumar1 aManu S. Pillai1 aYash Gupta1 aManju Khari1 aVicente García-Díaz1 aJavier Parra Fuente00aOptimizing Fast Fourier Transform (FFT) Image Compression using Intelligent Water Drop (IWD) Algorithm  uhttps://www.ijimai.org/journal/sites/default/files/2022-11/ijimai7_7_5.pdf  a48-550 v73 aDigital image compression is the technique in digital image processing where special attention is provided in decreasing the number of bits required to represent a digital image. A wide range of techniques have been developed over the years, and novel approaches continue to emerge. This paper proposes a new technique for optimizing image compression using Fast Fourier Transform (FFT) and Intelligent Water Drop (IWD) algorithm. IWD-based FFT Compression is a emerging ethodology, and we expect compression findings to be much better than the methods currently being applied in the domain. This work aims to enhance the degree of compression of the image while maintaining the features that contribute most. It optimizes the FFT threshold values using swarm-based optimization technique (IWD) and compares the results in terms of Structural Similarity Index Measure (SSIM). The criterion of structural similarity of image quality is based on the premise that the human visual system is highly adapted to obtain structural information from the scene, so a measure of structural similarity provides a reasonable estimate of the perceived image quality.  a1989-1660