In order to solve the problem that the edge of low-resolution laser image is easily disturbed by noise, which leads to a low critical visible deviation of the image edge, a low-resolution laser image edge inpainting method based on multi-view fusion and bilateral filtering is proposed. The bilateral filtering denoising model of low-resolution laser image is constructed, and the distribution set of image edge features is extracted by fusing multiple views through the method of depth confidence measurement. The visual communication model of the image is constructed by using the fusion processing method of depth map model parameters, and the image edge repair is realized according to the prior edge and texture information, and the adaptive optimization is carried out according to the correlation. The experimental results show that the proposed method can effectively restore the image edge, the average of the critical visible deviation of the image edge is increased to 28.90%, the number of pixels of the image edge that can be perceived by human eyes is increased, the average of the structural similarity is 0.981, the root mean square error is only 0.004 9, and the peak signal to noise ratio is 49.1 dB. The average running time is 4.8 s, which improves the effect of image edge inpainting and reduces the running time.