Evolution of New Integrated Haze Removal Algorithm Based On Haze Line
Meenu1, S andeep Kumar2, V.K.Panchal3, Rajeev Kumar4
1Meenu , Research Scholar , Mewar University, Chittorgadh, Rajasthan, India.
2S andeep Kumar, Research Scholar , Bhagwant University, Ajmer , Rajasthan, India.
3Dr.V.K.Panchal, Founder President, Computational Intelligence Research Group India.
4Dr. Rajeev Kumar, Associate Professor and Sr. Member of IEEE Collage of Computer Science and Information Technology TMU , Moradabad , India.
Manuscript received on July 20, 2019. | Revised Manuscript received on August 10, 2019. | Manuscript published on August 30, 2019. | PP: 184-189 | Volume-8 Issue-6, August 2019. | Retrieval Number: E7084068519/2019©BEIESP | DOI: 10.35940/ijeat.E7084.088619
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Haze is a standout amongst the most essential factor that debases the outside pictures. Picture corruption relies upon the separation of the Object from the camera as the separation increment from the camera of the scene point haze additionally increases. This paper presents a haze removal technique which is relies on the Haze-line prior that is recently introduced. This prior is based on the observation that the pixel values of a hazy image can be modeled as lines in RGB space that intersect at the air- light proposed approach is known as haze line. In this paper we proposed Post processing CBMG (Contrast, Brightness, Midtone and Gama adjustment) followed by four stages: clustering the pixel into haze line, Estimation of Transmission map, Regularization, Dehazing, This method is implement by observation of two basic things first pixels in a given group are regularly non local . Second pictures with improved perceivability (or sunny morning picture) have more differentiation than the pictures stopped by terrible climate. Experimental result demonstrate that our method remove haze layer and provide qualitative result.
Keywords: CBMG , Haze line , Non- local , RGB .