ANALISA METODE SHANNON ENTROPY DAN DIFFERENTIAL EVOLUTION UNTUK KOMPRESI GAMBAR - Adi Bayu Adnyana, I Komang; Oka Widyantara, I Made; Dewi Wirastuti, NMAE (Jurnal SPEKTRUM, 2021)
One of the most important phases in image storage is compression. Most current image compression methods are spatial. In this article, we present an image compression technique based on Multi-level Thresholding. The grayscale images are divided into groups based on the net probabilistic division. To determine the grouping uncertainty, Shannon Entropy is used. Optimization methods have also been added to obtain more optimal settings. Differential Evolution is an optimization technique. Image histogram is a graph that depicts the distribution of pixel intensity values of an image. Image compression performance measurement was measured using FSIM (Feature Similarity Index Measure) and SSIM (Structural Similarity Index Measure).