IMPROVING IMAGE QUALITY IN POOR VISIBILITY CONDITIONS USING A PHYSICAL MODEL FOR CONTRAST DEGRADATION

In daylight viewing conditions, image contrast is often significantly degraded by atmospheric aerosols such as haze and fog. This paper intr oduces a method for reducing this degradation in situations in which t he scene geometry is known. Contrast is lost because light is scattere d toward the sensor by the aerosol particles and because the light ref lected by the terrain is attenuated by the aerosol. This degradation i s approximately characterized by a simple, physically based model with three parameters. The method involves two steps: first, an inverse pr oblem is solved in order to recover the three model parameters; then, for each pixel, the relative contributions of scattered and reflected flux are estimated. The estimated scatter contribution is simply subtr acted from the pixel value and the remainder is scaled to compensate f or aerosol attenuation. This paper describes the image processing algo rithm and presents an analysis of the signal-to-noise ratio (SNR) in t he resulting enhanced image. This analysis shows that the SNR decrease s exponentially with range. A temporal filter structure is proposed to solve this problem, Results are presented for two image sequences tak en from an airborne camera in hazy conditions and one sequence in clea r conditions, A satisfactory agreement between the model and the exper imental data is shown for the haze conditions. A significant improveme nt in image quality is demonstrated when using the contrast enhancemen t algorithm in conjuction with a temporal filter.