Outdoor Image Enhancement: Increasing Visibility Under Extreme Haze and Lighting Condition
The problem of image enhancement thereby enhancement of scene visibility in outdoor images is handled. Visibility is a very important issue in case of computer based surveillance, crime analysis, driver assistance system design etc. The most important challenge related to visibility is the atmospheric haze and poor lighting. The problem becomes more challenging if haze is too dense and lighting during night is extremely poor. An automatic degradation detection and restoration algorithm has been proposed, which detects the type of degradation using the distribution of the scene, then uses the hybrid dark channel prior based haze removal algorithm if the image is degraded due to atmospheric haze only, otherwise it computes the image negative first and then uses the hybrid DCP to resolve the problem. The algorithm has been tested in many situations and the results obtained are satisfactory as comparison to the existing algorithms.
In the field of haze removal different methods are present which basically built on the priority of strong assumptions.
Tan and Fatal proposed different algorithms based upon the priority and their algorithm can enhance the hazy images appreciably.
Kiming He also proposed algorithm for single image haze removal using the dark channel prior method which is also based upon a strong priority and statistics of the outdoor haze-free images. The dark channel prior method is very useful to dehaze the hazy images
The dark channel method fails to enhance the sky regions where the sunlight is very influential. So in outdoor image case the dark channel prior method is inefficient to enhance the entire scene.
Practically in some physical conditions the assumed models may fail and may provide physically invalid output results.
Existing models may not enhance the extreme hazy images.
To propose a highly efficient and integrated algorithm to enhance both hazy outdoor images and the low light images i.e. taken in the night condition.
The proposed algorithm integrates both the algorithms for hazy image as well as the night images.
A new method is proposed where we integrate histogram equalization with the darkchannel prior method so as to de-haze the image as well as to increase the contrast of the image.
This proposed method utilizes the core de-haze algorithm and histogram equalization to enhance the outdoor images in extremely poor visibility condition.
Better visualization of outdoor images