A Framework to Detect Most Efficient Image Compression Technique on Cloud Storage

Abstract: Digital image compression technology is of special interest for the fast transmission and real-time processing of digital image. However image compression is a trend of research grown for a long time and there are multiple sophisticated approaches which significantly improve the compression rate and down grade computation time, a basic comparison with the aspect of storage on cloud environment is required. This work analyzes about the background of image compression, including when image compression is needed, categories of techniques and their properties. However compression uses many algorithms that store an exact representation or an approximation of the original image in a smaller number of bytes that can be expanded back to its uncompressed form with a corresponding decompression algorithm. This work majorly focuses on a novel framework for analyzing the impact of generic image compression techniques based on compression ratio and time for high data loads on cloud storage services and find the optimal set of algorithms most suitable for cloud storage. Keywords: DWT; K-Mean; 3D Spiral JPEG 2000; Cloud Storage Comparator; Microsoft Azure; Google Apps engine; Amazon Web Service; Cloud Storage.