Color percept is a subjective experience and, in general, it is impossible for other people to tell someone's color percept. The present study demonstrated that the simple image-classification analysis of brain activity obtained by a functional magnetic resonance imaging (fMRI) technique enables to tell which of four colors the subject is looking at. Our results also imply that color information is coded by the responses of hue-selective neurons in human brain, not by the combinations of red-green and blue-yellow hue components.

Image enhancement plays an important role in many machine vision applications on images captured in low contrast and low illumination conditions. In this study, we propose a new method for image enhancement based on analysis on embedded surfaces of images. The proposed method gives an insight into the relationship between the image intensity and image enhancement. In our method, scaled surface area and the surface volume are proposed and used to reconstruct the image iteratively for contrast enhancement, and the illumination of the reconstructed image can also be adjusted simultaneously. On the other hand, the most common methods for measuring the quality of enhanced images are Mean Square Error (MSE) or Peak Signal-to-Noise-Ratio (PSNR) in conventional works. The two measures have been recognized as inadequate ones because they do not evaluate the result in the way that the human vision system does. This paper also presents a new framework for evaluating image enhancement using both objective and subjective measures. This framework can also be used for other image quality evaluations such as denoising evaluation. We compare our enhancement method with some well-known enhancement algorithms, including wavelet and curvelet methods, using the new evaluation framework. The results show that our method can give better performance in most objective and subjective criteria than the conventional methods.

In this paper, we show that motion sharpening phenomenon can be explained as a form of visual masking for a special case where a video sequence is composed of alternate frames with different level of sharpness. A frame of higher sharpness behaves to mask the ambiguity of a subsequent frame of lower sharpness and hence preserves the perceptive quality of the whole sequence. Borrowing the mechanism for visual masking, we formulated a quantitative model for deriving the minimum spatial frequency conditions which preserves the subjective quality of the frames being masked. The quantitative model takes into account three fundamental properties of the video signals, namely the size of motion, average luminance and the power of each frequency components. The psychophysical responses towards the changes of these properties are obtained through subjective assessment tests using video sequences of simple geometrical patterns. Subjective experiments on natural video sequences show that more than 75% of viewers could make no distinction between the original sequence and the one processed using the quantitative model.

The present research examines the relationship between texture processing and object processing in human vision. Recent computational studies have suggested a difference between the stages of processing. Texture processing can be performed by using statistical parameterization of the response of primary spatial filters. Object processing requires more complex and elaborate computation at a higher stage than texture processing. Our psychophysical experiments are conducted to clarify the relationship of the stages of texture processing and object processing, by focusing on same-object effect which facilitates and speeds attention shifts within the same object and also costs and delays attention shifts if the attention focus moves from one object to another. Texture is composed of lines parallel to, perpendicular to or inside of elongated rectangles used as objects. The same-object effect is measured with reaction time in a cued detection task. Vertical rectangles are used in xperiment 1 and horizontal ones are used in Experiment 2. Experiment 1 shows that the texture lines interrupt the same-object effect and that the interruption is nearly equal if texture lines are added both to the background and the inside of the objects. Experiment 2 yields the result same as Experiment 1. The interruption of the same-object effect by adding texture lines suggests that texture processing affects object processing.

Texture has been investigated as a cue for reconstructing 3-D structure. There are various textures in a natural scene. In this paper, the regularity of alignment of texture elements was manipulated to investigate its effect on human perception. The results show that the regularity affects human perception when only the texel density gradient is given as cue or the density cue is inconsistent with the compression cue. We introduce a model based on a MAP estimation to account for the result from a viewpoint of an integration of 3-D cues. The model simultaneously estimates texture properties and 3-D surface orientation by using prior knowledge about texture and 3-D surface. The performance of the model accounts for the experimental result well.

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.

We can understand and recover a scene even from a picture or a line drawing. A number of methods have been developed for solving this problem. They have scarcely aimed to deal with scenes of multiple objects although they have ability to recognize three-dimensional shapes of every object. In this paper, challenging to solve this problem, we describe a method for deciding configurations of multiple objects. This method employs the assumption of coplanarity and the constraint of occlusion. The assumption of coplanarity generates the candidates of configurations of multiple objects and the constraint of occlusion prunes impossible configurations. By combining this method with a method of shape recovery for individual objects, we have implemented a system acquirig a three-dimensional information of scene including multiple objects from a monocular image.

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.