Review of Image Quality Assessment Methods for Compressed Images

Area of Science:

• Computer Vision
• Image Processing
• Digital Media

Background:

• Lossy image compression is essential for managing large datasets, balancing storage reduction with potential visual distortions.
• Perceptual quality evaluation is critical for standardizing efficient lossy compression methods.
• Compression artifacts like blocking, blurring, and color shifts vary based on content and compression levels.

Purpose of the Study:

• To investigate research queries for achieving visually lossless images.
• To analyze the impact of compression on image quality.
• To guide researchers in selecting optimal image quality assessment (IQA) methodologies.

Main Methods:

• Reviewing existing literature and surveys on image quality assessment (IQA).
• Evaluating the effectiveness of subjective assessment methods.
• Examining appropriate objective image quality metrics (IQMs).

Main Results:

• Compression significantly influences perceived image quality, introducing specific visual anomalies.
• Objective IQMs offer efficiency but subjective assessments remain the benchmark for perceptual quality.
• Challenges exist in current IQA methodologies, necessitating careful selection of assessment approaches.

Conclusions:

• Achieving visually lossless compression requires a nuanced understanding of both objective and subjective IQA.
• Researchers must consider trade-offs between assessment efficiency and accuracy.
• Further research is needed to refine IQA methods for diverse compression scenarios.