Abstract

This paper makes an investigation of the dehazing
effects on image and video coding for surveillance systems. The
goal is to achieve good dehazed images and videos at the receiver
while sustaining low bitrates (using compression) in the transmission
pipeline. At first, this paper proposes a novel method
for single-image dehazing, which is used for the investigation. It
operates at a faster speed than current methods and can avoid halo
effects by using the median operation. We then consider the dehazing
effects in compression by investigating the coding artifacts
and motion estimation in cases of applying any dehazing method
before or after compression. We conclude that better dehazing
performance with fewer artifacts and better coding efficiency
is achieved when the dehazing is applied before compression.
Simulations for Joint Photographers Expert Group images in
addition to subjective and objective tests with H.264 compressed
sequences validate our conclusion

Implementation

The project will be implemented on MATLAB GUI. Dark Channel Priority (DCP) algorithm is designed using mfile.Here the paper was implemented by image and video.
Then modified DCP algorithm was developed .Result was obtained Median Dark Channel Priority(MDCP) and minimum Dark Channel Priority(DCP) with image and video coding