Rapidly growing use of multimedia products in diagnosis is affected by insufficient network and computer storage, as most of these applications use images of large data size. Compression is also important for reducing the size of images, particularly at lower bit rates, and it helps to avoid the use of additional memory and bandwidth in cloud storage. Image compression is classified into two types: lossy compression and lossless compression. The lossy compression technique can be used for medical image diagnosis while maintaining decoded image quality and achieving a high compression ratio, thus increasing device efficiency and reducing network bandwidth for transmission. In this paper, we propose a novel lossy colour image compression approach based on multi transforms such as DWT, SWT, and curvelets. The proposed work focused on an image compression technique based on DWT interpolation of high frequency sub-bands, correction of high frequency sub-band estimation using SWT high frequency sub-band and curvelets and comparison of the resulting images to current lossy compression techniques. Multi transforms compressed images have a high compression rate while maintaining good image quality.