No-Reference Image Quality Assessment Algorithm BIQI

In the field of image quality assessment, the BIQI algorithm is a commonly used no-reference image quality assessment method. The algorithm evaluates image quality by analyzing and comparing specific features extracted from the image. It employs a two-stage framework that first classifies distortion types and then performs distortion-specific quality assessment. Key technical components include wavelet domain natural scene statistic (NSS) feature extraction, support vector machine (SVM) based distortion classification, and quality prediction models for various distortion types such as blurring, noise, and compression artifacts. The algorithm can detect common image impairments including distortion, blur, noise, and other quality degradation factors, providing corresponding quality scores. Implementation typically involves MATLAB-based feature extraction using wavelet decomposition, followed by machine learning-based quality prediction. Therefore, using the BIQI no-reference image quality assessment algorithm helps us comprehensively understand image quality conditions, enabling corresponding improvements and optimizations in image processing pipelines.