Low Resolution 3D Image Enhancement Based on Artificial Neural Network

In order to improve the quality of low resolution 3D images, this study proposes a low resolution 3D image enhancement method based on artificial neural network. First of all, the adjustable filter is used to divide the image categories, and the multi-angle mesh model of the machine vision system is constructed. Then, the low resolution image is decomposed into multiple scales by filtering method. The white balance method is used to eliminate the color deviation of low resolution 3D images and realize the color correction of low resolution 3D images. Finally, the atmospheric scattering model is used to de blur the low resolution 3D image. Combining the advantages of color model transformation algorithm and artificial neural network, the low resolution 3D image enhancement algorithm is designed. Experimental results show that this method can improve the quality of low resolution 3D images and enhance the image enhancement effect.