Authors : Khamees Khalaf Hasan, Ibrahim Khalil Salih and Kamil Jadoaa Ali
Abstract: For future wireless access technologies, the furthermost significant challenges will be the requirement to process and transmit a huge volume of image data wirelessly. One method to relieve this difficulty is by compression techniques to decrease the magnitude of transmitted image data over the wireless channel. Discrete Cosine Transform DCT utilized as a kernel transform coding of Joint Photographic Experts Group (JPEG) compression technique. DCT packing the image signal energy into few numbers of transformed coefficients associated with low frequencies. The high frequency coefficients may be discarded with little loss in image signal energy and that will not effect that much on the reconstructed image quality, since, the human eye doesn’t sense the high frequency components. Using a modified version of JPEG according to the energy requirement of Visual Sensor Network VSN an adapted JPEG method is proposed. This involves the concept of processing only the low frequency portion of each block of the DCT coefficients of a given image. The compression algorithm in the proposed JPEG scheme minimizes the computational complexity and reduces the required energy consumption needed to transmit an image while it allows a trade-off between image distortion using Peak Signal to Noise Ratio PSNR metric and Compression Ratio CR. When the number of retained useful low frequency coefficient is 30% and less, the reconstructed images shows a noticeable degradation at all which can be used to counter severe hardware constraints of various wireless devices applications.
Khamees Khalaf Hasan, Ibrahim Khalil Salih and Kamil Jadoaa Ali, 2019. Efficient Energy Consumption DCT-Based Image Compression in Visual Sensor Network. Journal of Engineering and Applied Sciences, 14: 3719-3727.