Foggy image enhancement using contrast limited adaptive histogram equalization of digitally filtered image: Performance improvement

Abstract

Digital filters are used in signal processing to improve the quality of signal and to remove/reduce noise. Fog is a type of unwanted signal which create visuality difference between object and viewer. For removing this type of unwanted signal, digital filters are used. Digital filter is divided into two parts: finite impulse response (FIR) and infinite impulse response (IIR). The author introduced a new approach for improving the quality of foggy image and to increase peak signal to noise ratio. In this paper author used finite impulse response filter for foggy image which work over zero to finite time interval. In FIR filter, separable filter coefficients are used which reduce the amount of calculation. For improving image contrast hgamma correction function is used. After contrast adjustment of input image, contrast limited adaptive histogram equalization (CLAHE) is applied over an image and produce an enhanced image. The main aim of this paper is to improve the quality of foggy image using digital FIR filter and contrast limited adaptive histogram equalization. We also compare previous algorithms in this field through implementation of the methods keeping same parameter for critical analysis. In the end of this article author provide the future scope for working direction.