Objective assessment of image and video quality should be based on a correct understanding of subjective assessment by human observers. Previous models have incorporated the mechanisms of early visual processing in image quality metrics, enabling us to evaluate the visibility of errors from the original images. However, to understand how human observers perceive image quality, one should also consider higher stages of visual processing where perception is established. In higher stages, the visual system presumably represents a visual scene as a collection of meaningful components such as objects and events. Our recent psychophysical studies suggest two principles related to this level of processing. First, the human visual system integrates shape and color signals along perceived motion trajectories in order to improve visibility of the shape and color of moving objects. Second, the human visual system estimates surface reflectance properties like glossiness using simple image statistics rather than by inverse computation of image formation optics. Although the underlying neural mechanisms are still under investigation, these computational principles are potentially useful for the development of effective image processing technologies and for quality assessment. Ideally, if a model can specify how a given image is transformed into high-level scene representations in the human brain, it would predict many aspects of subjective image quality, including fidelity and naturalness.

A new gloss-extracting method is proposed in this study. A spatial filter with variable resolution is used for the extraction of glossiness. Various spheres and cylinders with curvature radii from 4 to mm are used as the specimens. In all samples, a strong correlation, with a correlation coefficient of more than 0.98, has been observed between psychological glossiness Gph perceived by the human eye and glossiness Gfm extracted by this method. This method is useful for plane specimens as well as spherical and cylindrical ones.

Although the perception of gloss is based on human visual perception, some methods for extracting glossiness, in contrast to human ability, have been proposed involving curved surfaces. Glossiness defined in these methods, however, does not correspond with psychological glossiness perceived by the human eye over the wide range from relatively low gloss to high gloss. In addition, the obtained glossiness in these methods changes remarkably when the curvature radius of the high-gloss object becomes larger than 10mm. In reality, psychological glossiness does not change. These methods, furthermore, are available only for spherical objects. A new method for extracting glossiness is proposed in this study. For the new definition of glossiness, a spatial filter which simulates human retina function is utilized. The light intensity distribution of the curved object is convoluted with the spatial filter. The maximum value Hmax of the convoluted distribution has a high correlation with psychological glossiness Gph. From the relationship between Gph and Hmax, new glossiness Gf is defined. The gloss-extraction equipment consists of a light source, TV camera, an image processor and a personal computer. Cylinders with the curvature radii of 3-30 mm are used as the specimens in addition to spherical balls. In all specimens, a strong correlation, with a correlation coefficient of more than 0.97, has been observed between Gf and Gph over a wide range. New glossiness Gf conforms to Gph even if the curvature radius in more than 10 mm. Based on these findings, it is found that this method for extracting glossiness is useful for the extraction of glossiness of spherical and cylindrical objects over a wide range from relatively low gloss to high gloss.

The already reported physical glossiness such as Mirror glossiness, indistinctness-degree glossiness, etc. are not proportional to the psycological glossiness which is the standard of the gloss, in cases of various colored specimens. Thus, in order to obtain a glossiness proportional to the psycological glossiness, first, the brightness distribution of the colored specimens was measured. Then, it was transformed to bring the form of the measured brightness distribution close to the visual distinctness-begree distribution, by the expand-reduce transformation technique. From the transformed distribution curve, the new glossiness G(H, V, C) was defined as functions of hue H, lightness V, saturation C and the indistinctness-degree glossiness GID. This new glossiness G(H, V, C) was applied to the Munsell color atlas papers and the high glossy colored papers, and then it was confirmed to be in proportion to the psychological glossiness GPh.

Although the perception of gloss is based on human visual perception, some methods for measuring glossiness, in contrast to human ability, have been proposed involving plane surfaces. Glossiness defined in these methods, however, does not correspond with psychological glossiness perceived by the human eye over the wide range from relatively low gloss to high gloss. In addition, the change in the incident angle causes a deviation in the measurement of glossiness. A new method for measuring glossiness is proposed in this study. For the new definition of glossiness Gd, the brightness function is utilized. We also extract the value of smoothness of the object's surfaces for use as a factor of glossiness. The measuring equipment consists of a light source, an optical system and a personal computer. Glossiness Gd of paper and plastics is measured with the use of this equipment. In all samples, a strong correlation, with a correlation coefficient of more than 0.97, has been observed between Gd and psychological glossiness Gph. The variance of measured glossiness due to the change in the incident angle of light is small in comparison with that of conventional methods. Based on these findings, it has been found that this method is useful for measuring glossiness of plane objects in the range from relatively low gloss to high gloss.