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Deep learning based image resolution reconstruction has gained popularity recently. Using sensors, underwater pictures are captured. Due to the water's exponential attenuation of the transmitted light, underwater photographs have poor visibility, including low contrast and color blurring. The identification of targets and further evaluation are made more difficult by the underwater images' degradation. This paper offers a hybrid underwater image processing method called deep learning based transmission binary mapping algorithm that combines a color balance algorithm with an underwater picture restoration technique to solve these issues. This research work proposes an enhanced picture super-resolution reconstruction approach. It is based on transmission based binary mapping algorithm for enhancement in the efficiency of machine learning concepts. To calculate transmission maps, RGB attenuation for each …