A novel Image Security Protection Method Based on DCT Compression Theory and Hyper-chaotic Mapping

This paper studies the current situation of image compression encryption and analyzes the influence of low frequency (DC coefficient) and high frequency (AC coefficient) on image structure in DCT transformation. Based on this, a novel image security protection method based on DCT compression theory and hyper-chaotic mapping is proposed. First, the position of the pixel of the original image is disturbed, and converts the image from spatial domain into frequency domain by the two-dimensional DCT transformation and quantization. Second, change the pixel values by modifying the values of the sign bit of AC coefficient and DC coefficient. At last, the encrypted image is obtained by carrying out inverse quantization, inverse transformation and reverse operation by bit.

Low Complexity DCT Approximation for Image Compression in Wireless Image Sensor Networks

Energy consumption is a critical problem affecting the lifetime of wireless image sensor networks (WISNs). In such systems, images are usually compressed using JPEG standard to save energy during transmission. And since DCT transformation is the most computationally intensive part in the JPEG technique, several approximation techniques have been proposed to further decrease the energy consumption. In this paper, we propose a low-complexity DCT approximation method which is based on the combination of the rounded DCT with a pruned approach. Experimental comparison with recently proposed schemes, using Atmel Atmega128L platform, shows that our method requires less arithmetic operations, and hence less processing time and/or the energy consumption while providing better performance in terms of PSNR metric.