Underwater image classification based on image enhancement and information quality evaluation1

Underwater target imaging is widely used in oceans, rivers and lakes detection fields, but due to the existence of water on light absorption scattering attenuation effect, the diffraction limit of imaging system, aberration distortion and underwater turbulence, underwater images has serious degradation, mainly manifested in noise, fuzzy and low resolution, etc. In recent years, some scholars have started from the image enhancement and restoration to improve the image degradation and improve the image clarity, but the effect still needs to be improved, and the resolution can not be improved, and some algorithms will even reduce the resolution.Resolution is an important parameter for the image evaluation, improving the image quality in the underwater imaging, especially in the human eye vision, which is largely determined by the improved resolution. Therefore, this paper starts from each aspects of image processing, studies, proposes and experiments a large number of image recovery algorithms. This paper analyzes various factors introducing noise in underwater imaging process, proposes block mixed filter image denoising method based on noise statistical characteristics, analyzes the necessity of evaluating image quality by using objective indicators, and gives the corresponding objective evaluation parameters according to the characteristics of the image recovery algorithm. According to the noise preprocessing method and the image quality evaluation method, the underwater image synthesis dataset is screened to improve the performance of the underwater object recognition model.