Interim connection space based on colorimetric values for spectral image compression and reproduction

Area of Science:

• Color Science
• Image Processing
• Computer Vision

Background:

• Accurate spectral reconstruction is crucial for digital imaging and color reproduction.
• Existing interim and connection spaces (ICS) often struggle with precise colorimetric matches under real-world illuminants.

Purpose of the Study:

• To introduce a new ICS, tD65A, and a reconstruction method for improved spectral accuracy.
• To achieve exact colorimetric matches under CIE illuminants D65 and A.
• To enhance spectral and colorimetric accuracy in reconstructed reflectance.

Main Methods:

• Developed the tD65A ICS using six colorimetric values under CIE illuminants D65 and A.
• Introduced a new spectral decomposition based on tD65A ICS and Wiener Estimation matrix (MW).
• Trained basis vectors for metameric black space and a polynomial mapping matrix (MP,k) for enhanced accuracy.

Main Results:

• The tD65A ICS ensures exact colorimetric matches under D65 and A illuminants.
• Performance tests showed superior spectral accuracy (RMSE, GFC) and colorimetric accuracy (CIEDE2000) compared to five other ICSs.
• Outperformed existing methods across continuous, fluorescent, and LED illuminants.

Conclusions:

• The proposed tD65A ICS and reconstruction method offer significant improvements in spectral accuracy.
• The method provides exact colorimetric matches, a key advantage over other ICSs.
• Expected to be valuable for spectral image compression and reproduction applications.