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5 June 2018 Optimization of the uniformity of brightness distribution of abstract images with a high degree of self-similarity
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Abstract
Methods of creating a natural environment are increasingly used to reduce stress in the workplace and increase productivity. When an artificial visual environment is created, it is important that the degree of self-similarity of the images approximates the values characteristic of the natural environment. It should be noted that the degree of selfsimilarity of the visual environment that surrounds a person in everyday life (in an office, in an urban environment) is usually low, and natural landscapes have a high degree of self-similarity. A visual environment with a high degree of self-similarity can be obtained by passing laser radiation through optically inhomogeneous media or objects of complex shape with a small-sized chaotic structure. The images obtained in this way have a natural structure in a certain sense, because they are based on the effects of interference and dispersion (i.e. natural). However, in our experiments the resulting image has areas of great brightness. The eye adopts precisely for the perception of these parts of the image, and the most interesting part of its structure can be out of the range of perception, which denies the efforts to make such an image. We analyze possible ways of solving this problem and get a complex image of the structure without sharp changes in brightness. The main task here is to select the parameters of the complex object and the parameters of the laser beam so that the object can be made without using special microtechnologies and at the same time obtain the desired image.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Nikolai V. Matveev, Galina E. Romanova, Irina Ampleeva, and Alena Guseva "Optimization of the uniformity of brightness distribution of abstract images with a high degree of self-similarity", Proc. SPIE 10690, Optical Design and Engineering VII, 106902B (5 June 2018); https://doi.org/10.1117/12.2312055
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