Method of Processing Closed-Circuit Television Digital Images for Poor Visibility Identification

Abstract

This study proposes a method for identifying poor visibility under adverse weather conditions by processing closed-circuit television (CCTV) digital images. The weighted intensity of the power spectrum (WIPS) was examined to determine its applicability as a value for the identification of poor visibility. The magnitude of WIPS represents the difference in spatial frequencies within the image on the basis of the human contrast sensitivity function. WIPS was calculated by the following image-processing procedure: the spatial frequency of the cutout image was calculated with a two-dimensional Fourier transform, and the power spectrum of the cutout image was calculated; WIPS was totaled at spatial frequencies that ranged from 1.5 to 18 cycles per degree. Two kinds of experiments were performed to determine whether WIPS represented the subjective visibility assessment values (SVAVs) given by the test subjects. Clear linear relationships between WIPS and SVAVs were found in both experiments. In addition, the two correlation lines overlapped within the whole range of WIPS. These results suggest that WIPS may be appropriate for identifying poor visibility by the use of digital images.