The surface appearance of products affects buying intention. In particular, image clarity is an important appearance quality factor that aﬀects the elegance of the products, for example, automobile and smartphone. The correlation between the conventional evaluation methods and visual inspection is poor. In addition, these methods damage the surface of products due to a contact measurement. The purpose of paper is to develop a new image clarity evaluation method that is high correlation with visual inspection and a non-contact measurement for solid and metallic color samples. To develop the new image clarity evaluation method, ﬁrst, the measurement device composed of a spectral camera and a lighting device for projecting an edge pattern on an object was constructed. Next, subjective experiments on image clarity were conducted using Sceffeʼs paired comparison. The new evaluation model based on the spatial frequency characteristic of the projected pattern image and human visual characteristic was proposed. Furthermore, the surface color was added to the model. As a result, the contribution ratio of the new evaluation model and the subjective score was very high.
Tracing the evolution of mammals，our common ancestor, vertebrates were originally tetrachromat, but retreated to nocturnal dichromat in the Mesozoic dinosaurs age. The primates regained the diurnal after the extinction of dinosaurs. About 35 million years ago, human beings won the LMS trichromacy by mutations in the gene duplication process. Birds are typical tetrachromat with the fourth UV cone and a valuable taxon that inherits the color vision of our common ancestors now. It's interesting if possible to glimpse the UV world from the color vision of birds that our anchesters were seing.
In this paper, we extend the Matrix-R theory to tetrachromacy and try to estimate "how Leiothrix lutea sees the UV world with ROGU cone sensors? ". The extended matrix R4, which is created from the basis functions of ROGU, projects an input spectrum C(λ)onto FCS(Fundamental Color Space)of Leiothrix lutea. The matrix R4 extracts the spectrum C*4(λ)called "fundamental " from C(λ),that is, visible to Leiothrix lutea. First, tetra-chromatic ROGU stimulus in a scene is estimated from tri-chromatic sRGB camera image by a simple linear model. Next, the fundamental C *4(λ)is restored by the pseudo-inverse projection of ROGU stimulus. Finally, C *4(λ)is separated to four-color channels of(Red, Orange,Green, and UV)and the UV channel is visualized by colorization. A true fundamental C *4(λ)is calculated by operating the matrix R4 onto a measured real spectrum C(λ)and is examined how it matches with the estimated C *4(λ).