International Journal of Image, Graphics and Signal Processing (IJIGSP)
IJIGSP Vol. 16, No. 6, 8 Dec. 2024
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Underwater Image Refinement: Color Distance and Image Formation Model (DIMFM)
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Author(s)
Shivani Gaikwad
1
Sachin Patil
2,*
Index Terms
Image Processing, Dehazing, Light Intensity, Visibility Restoration
Abstract
Underwater photography is frequently used for research purpose in various domains. Domains caters to archaeology, surveillance of aquatic life movements, oceanic changes leading to alterations in weather and many more. Scientists are eager to investigate the mysterious undersea environment. For underwater surveys, archaeology departments and weather forecasting scientists obtain undersea photos. The underwater imagery however has low vision and contrast due to haze. The elimination of haze could be difficult because it depends on depth information that is unclear. Moreover, it’s challenging and complicated to clear the haze so as to enhance the underwater image. According to the investigation, fog removal algorithms currently in use do not take noise reduction approaches into account. Dehazing techniques have a hard time dealing with areas that are unevenly and excessively light. Therefore, it is vital to alter current techniques in order to make them more efficient. This work presents an innovative integrated underwater picture restoration technique. The proposed technique is in line to a pre-determined technique namely Underwater Image Formation Model. The new approach combines Bilateral Filtering, Contrast Limited Adaptive Histogram Equalization and Dark Channel Prior for better results. First, the underwater image undergoes bilateral filtering to eliminate color discrepancies. The improved image is output of the differentiation between forward and background channel. Further, the Contrast Limited Adaptive Histogram Equalizations methodology is used to produce contrast-enhanced images. Experimental results signpost that the proposed novel technique generates superior visual effects compared to other widely used undersea color image quality evaluation techniques.
Cite This Paper
Shivani Gaikwad, Sachin Patil, "Underwater Image Refinement: Color Distance and Image Formation Model (DIMFM)", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.16, No.6, pp. 1-16, 2024. DOI:10.5815/ijigsp.2024.06.01
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