Aiming at the problems of the current capsule endoscope, such as low resolution, limited field of view, and great influence by noise, a system solution was proposed. First, by introducing Q-type aspheric surface to correct aberrations, an endoscope imaging lens with a full field of view of 160°, a relative aperture of F#3.0, and a total system length of 4.3mm was finally obtained. MTF values at 140 lp/mm were all greater than 0.3. The imaging quality of an optical system depends not only on the performance of the lens, but also on the image sensor, especially in low-light environments. The noise model was obtained by analyzing the noise characteristics of each stage when the sensor was working. Using the established noise model, the capsule endoscope image data set was synthesized, and the neural network model was trained. The test results of the algorithm model show that the proposed comprehensive solution can effectively improve the imaging quality of capsule endoscope system.