Contrast degradation for improving quality of an image

The contrast of images is degraded due to atmospheric aerosols such as haze and fog. Contrast is lost due to scattering of light towards sensor by the aerosol particle. The effect of such aerosols is to reduce image contrast with increasing distance. The level of contrast reduction increases with the distance from the camera to the object. Histogram equalization method is useful for enhancing image contrast. This paper introduces a method for reducing this degradation. It involves two steps: first, an inverse problem is solved in order to recover the model parameters; then for each pixel, the relative contributions of scattered and reflected flux are estimated. The estimated flux is subtracted from the pixel value and the remainder is scaled to compensate for aerosol attenuation. The proposed algorithm has four stages: estimation of imaging parameters, model based contrast enhancement, estimation of local signal to noise ratio (SNR), and temporal filtering. A significant improvement in image quality is seen when using the contrast enhancement algorithm in conjunction with a temporal filter structure proposed. SNR also decreases exponentially with range. The resulting image quality is better than that which can be achieved using conventional techniques such as histogram equalization.