Referenceless image evaluation method for capsule endoscope, electronic device, and medium

A referenceless image evaluation method for a capsule endoscope, comprising:

• inputting original images into a preset image quality evaluation model and a preset image content evaluation model, so as to acquire image quality evaluation scores and image content evaluation scores corresponding to the original images;
• and
• determining, according to weights of the image content evaluation scores and weights of the image quality evaluation scores, a comprehensive score for each image currently being evaluated;
• wherein a method for constructing the image quality evaluation model comprises:
• analyzing each of the original images to extract a corresponding image quality evaluation characteristic value, wherein the image quality evaluation characteristic value comprises:
• at least one of a proportion fb1 of a first overexposed pixel,
• a proportion fb2 of a first dark pixel,
• a proportion fb3 of a high-frequency coefficient, and
• a characteristic value fbri obtained by a BRISQUE (Blind/Referenceless Image Spatial Quality Evaluator) algorithm;
• and
• dividing each of the original images into a first training set and a first testing set according to a predetermined ratio, training data of the first training set by using a support vector machine, and
• verifying by using data of the first testing set to obtain the image quality evaluation model,
• wherein, both the data of the first training set and the data of the first testing set comprise image quality calculation scores and image quality evaluation characteristic values corresponding to the original images;
• wherein before analyzing each of the original image to extract the corresponding image quality evaluation characteristic value, the method further comprises:
• clipping the original image at a preset size [W, H] with the center of the original image as a center point to obtain a preprocessed image for quality evaluation for the purpose of extracting the image quality evaluation characteristic value,
• and wherein, W∈[¼*M, ⅚*M], HE [¼*N, ⅚*N], [M, N] represent the size of the original image;
• after analyzing the preprocessed image for quality evaluation to extract the corresponding image quality evaluation characteristic value, the method further comprises:
• normalizing each of the image quality evaluation characteristic value into a corresponding preset normalization interval.