Super resolution imaging via sparse interpolation in wavelet domain with implementation in DSP and GPU

Abstract

This paper focuses on a novel image resolution enhancement method employing the wavelet domain techniques and hardware implementation of designed framework. In novel resolution enhancement approach for better preservation of the edge features, additional edge extraction step is used employing high-frequency (HF) sub-band images - low-high (LH), high-low (HL), and high-high (HH) - via the Discrete Wavelet Transform (DWT). In the designed procedure, the low resolution (LR) image is used in the sparse interpolation for the resolution-enhancement obtaining low-low (LL) sub-band. An efficiency analysis of the designed and other state-of-the-art filters have been performed on the DSP TMS320DM648 by Texas Instruments through MATLAB’s Simulink module and on the video card (NVIDIA Quadro K2000), demonstrating that novel SR procedure can be used in real-time processing applications. Experimental results have confirmed that implemented framework outperforms existing SR algorithms in terms of objective criteria as well as in subjective visual perception, justifying better image resolution.