On the Analysis of Wavelet-Based Approaches for Print Grain Artifacts

摘要

Grain is one of several attributes described in ISO/IEC TS 24790, a technical specification for the measurement of image quality for monochrome printed output. It defines grain as aperiodic fluctuations of lightness greater than 0.4 cycles per millimeter, a definition inherited from the latest official standard on printed image quality, ISO/IEC 13660. Since this definition places no bounds on the upper frequency range, higher-frequency fluctuations (such as those from the printer's halftone pattern) could contribute significantly to the measurement of grain artifacts. In a previous publication, we introduced a modification to the ISO/IEC 13660 grain measurement algorithm that includes a band-pass, wavelet-based, filtering step to limit the contribution of high-frequency fluctuations. This modification improves the algorithm's correlation with the subjective evaluation of experts who rated the severity of printed grain artifacts. Seeking to improve upon the grain algorithm in ISO/IEC 13660, the ISO/IEC TS 24790 committee evaluated several graininess metrics. This led to the selection of the above wavelet-based approach as the top candidate algorithm for inclusion in a future ISO/IEC standard. Our recent experimental results showed r2 correlation of 0.9278 between the wavelet-based approach and the subjective evaluation conducted by the ISO committee members based upon 26 samples covering a variety of printed grain artifacts. On the other hand, our experiments on the same data set showed much lower correlation (r2 = 0.3555) between the ISO/IEC 13660 approach and the same subjective evaluation of the ISO committee members. In addition, we introduce an alternative approach for measuring grain defects based on spatial frequency analysis of wavelet-filtered images. Our goal is to establish a link between the spatial-based grain (ISO/IEC TS 24790) approach and its equivalent frequency-based one in light of Parseval's theorem. Our experimental results showed r2 correlation near 0.99 between the spatial and frequency-based approaches.