An FPGA Based Practical Implementation of Stochastic Resonance For Image Enhancement

EasyChair Preprint no. 960

Abstract

In this paper, a non-linear non-dynamic stochastic resonance (SR) based technique is proposed for enhancement of dark and low contrast images. Noise-enhanced signal processing theory is applied to a low contrast image to improve the contrast. Insufficient illumination is the major cause of low contrast of the image, which can be stated as internal noise. This internal noise is neutralized by the addition of some pre-calculated external noise. The low contrast image is added to different frames of random noise and is thresholded repeatedly against a fixed parameter. After that, averaging produces a high contrast (enhanced) image. Noise-induced resonance is obtained at a particular optimum noise intensity. This optimum intensity is obtained by varying the noise intensities. Performance of the proposed technique is investigated for Gaussian noise. Quantitative evaluation of the performance is done in terms of color enhancement, contrast enhancement factor, and perceptual quality measure.

Furthermore, a hardware implementation of the proposed SR algorithm using NEXYS 4 DDR Artix-7, which is a low power FPGA device is done to show and validate the performance of the proposed algorithm in a practical environment. Power consumption and resource utilization of the proposed algorithm is also addressed. Finally, three different quantitative parameters \textit{i.e.,} contrast enhancement factor (F), color enhancement factor (CEF) and perpetual quality metric (PQM) are calculated to compare the hardware and software result of the proposed method.

Keyphrases: FPGA, image enhancement, stochastic resonance

@Booklet{EasyChair:960,
  author = {Sumit Kumar and Sudha Chauhan and Gaurav Sundaram and Mausam Chouksey and Rajib Kumar Jha},
  title = {An FPGA Based Practical Implementation of Stochastic Resonance For Image Enhancement},
  howpublished = {EasyChair Preprint no. 960},

  year = {EasyChair, 2019}}