Correlating objective and subjective evaluation of texture appearance with applications to camera phone imaging

Abstract

Texture appearance is an important component of photographic image quality as well as object recognition. Noise cleaning algorithms are used to decrease sensor noise of digital images, but can hinder texture elements in the process. The Camera Phone Image Quality (CPIQ) initiative of the International Imaging Industry Association (I3A) is developing metrics to quantify texture appearance. Objective and subjective experimental results of the texture metric development are presented in this paper. Eight levels of noise cleaning were applied to ten photographic scenes that included texture elements such as faces, landscapes, architecture, and foliage. Four companies (Aptina Imaging, LLC, Hewlett-Packard, Eastman Kodak Company, and Vista Point Technologies) have performed psychophysical evaluations of overall image quality using one of two methods of evaluation. Both methods presented paired comparisons of images on thin film transistor liquid crystal displays (TFT-LCD), but the display pixel pitch and viewing distance differed. CPIQ has also been developing objective texture metrics and targets that were used to analyze the same eight levels of noise cleaning. The correlation of the subjective and objective test results indicates that texture perception can be modeled with an objective metric. The two methods of psychophysical evaluation exhibited high correlation despite the differences in methodology.

Adapting the ISO 20462 softcopy ruler method for online image quality studies

“…This is discussed further with respect to Figure 12 and following. In order to compare our study's results with those of the original ISO 20462 softcopy quality ruler method, the data for the four scenes were combined for each treatment level (This averaging approach was utilized in the original reference paper [4] and was found to be useful and clearer for visual comparison). Figure 12 is a comparison of the averaged values for the reference SQS 2 JND values those from our Internet-based method.…”

“…As part of the Camera Phone Image Quality (CPIQ) initiative, the softcopy quality ruler method was validated in a study of image texture loss due to digital image processing [4]. Ten scenes were selected from the ISO 20462 Part 3 available rulers.…”

Texture MTF from images of natural scenes

“…it's a fractal) meaning that its characteristics do not vary with viewing distance [14] [17]. The texture-MTF has been proven to have good correlation with human perception of texture sharpness [18]. To better simulate a natural texture, the target was also designed to have a power spectrum close to an inverse power function (1/f n ), typical of natural scenes [17].…”

Softcopy quality ruler method: implementation and validation

“…Eight levels of noise cleaning were applied to those scenes, resulting in different levels of image quality. A companion paper [8] will provide further details on the test image manipulation and the experimental procedures. It should be noted that the validation study used a set of ruler images created for a viewing distance of 43in instead of 34in.…”