Abstract
AbstractAs communication networks evolve, so does the technology for exchanging and transmitting information. With millions of photos uploaded on social media every day, wireless sensor networks are rapidly being utilized to take images in a variety of applications such as traffic lights, roadways, social media, assembly, websites, and malls. As a result, it is required to reduce the size of these photos while retaining a suitable degree of quality. To compress RGB photos in this study, we used the K-mean clustering algorithm. Image quality is evaluated using after image compression, PSNR, MSE, and SSIM. The higher the K in the SSIM index, the more comparable the two photos are. This is a good sign that the image size has been greatly reduced. The proposed compression approach, which is based on the KMean clustering algorithm, is used to compress photos to minimize their size, server burden, and data transmission speed.KeywordsRGB imagesImage compressionk-Mean clusteringMean square error (MSE)Structural similarity index measure (SSIM)Peak signal-to-noise ratio (PSNR)MallsClusteringSocial mediaWebsites
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