The agile growth and demand of high quality multimedia has been raised drastically in last half decade. To storage and process this huge data over internet is a big challenge. Efficient transmission with less storage space demands the compression for such type of data. The performance of compression is closely related to the performance of any mathematical transforms in terms of energy compaction and spatial frequency isolation by majorly exploiting inter-pixel redundancies. The Fractional Fourier Transform (FRFT) is the generalization of the Fourier transform which may use in signal compression due to its property of establishing high correlation among the coefficients and its beauty of compact signal representation in FRFT domain along with noise immunity. The Discrete Fractional Fourier Transform (DFRFT) is derived form of Discrete Fourier transforms (DFT). In this article, a compression scheme based on Discrete Fractional Fourier Transform is proposed with superior performance over Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), and other Fractional Transforms based Compression schemes. The convincing feature of discrete fractional transforms is that it benefitted us with an extra degree of freedom that is provided by its fractional orders. In this scheme, an image is subdivided and DFRFT is applied on each subdivided image to transformed coefficients and quantize these transformed coefficients with reduced size subsequently, run length encoding is applied for further compression. Later, decompression is achieved by applying decoding and reverse order DFRFT on each sub-images and reconstruction of original image is done by merging all sub-images. The performance of the proposed scheme is evaluated on parameters, such as Peak Signal-to-Noise Ratio (PSNR), Mean Square Error (MSE), and Compression Ratio (CR) using MATLAB software environment.