A novel hybrid approach to enhance low resolution images using particle swarm optimization

Abstract

Enhancement of low resolution images is always a priority Enhancement of low resolution images is always a priority field of digital image processing. In this paper, we propose a novel hybrid approach based on discrete wavelet transform (DWT) and particle swarm optimization (PSO). To develop the proposed method we use spatial domain as well as frequency domain. To reduce the low frequencies from the input image we use the frequency domain. DWT is used to decompose the input low resolution image into different sub bands. Each of the interpolated high frequency sub band (LH, HL, HH) is then summed up with the interpolated output image of the frequency domain. In order to achieve high resolution image, the estimated high frequency sub bands of the intermediate stage and the interpolated low resolution input image have been combined by using inverse DWT. To generate a better high resolution image particle swarm optimization (PSO) technique has been used. The quantitative (root mean square error, normalized cross correlation, normalized absolute error) and visual outcome show the strength of this proposed method.