Sensuous Assesment Function of Images Based on Local Entropy Flow
| Project/Area Number |
60580026
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| Research Category |
Grant-in-Aid for General Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Research Field |
Informatics
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| Research Institution | Faculty of Engineering, Kobe University |
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Principal Investigator |
TANAKA Hatsukazu Faculty of Engineering, Kobe University Associate Professor, 工学部, 助教授 (80031144)
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| Project Period (FY) |
1985 – 1986
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| Project Status |
Completed (Fiscal Year 1986)
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| Budget Amount *help |
¥2,200,000 (Direct Cost: ¥2,200,000)
Fiscal Year 1986: ¥200,000 (Direct Cost: ¥200,000)
Fiscal Year 1985: ¥2,000,000 (Direct Cost: ¥2,000,000)
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| Keywords | Images / Local Entropy Flow / Principle of Constant Entropy / Entropy Filter / 感覚的評価関数 |
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| Research Abstract |
The main object of this research is to define the sensuous assesment function of images using a new concept of local entropy flow, and to develop a new sensuous coding scheme of images. First, a new concept of local entropy flow is introduced, and its quantitative definition is applied to some artificial images. The obtained entropy flow is plotted by three dimensional representation from which the validity of the above definition is certified. Next, we define a new concept of entropy filter which controls the parameter of the conventional low pass filter for images according to each value of the local entropy flow. Then the entropy filter is applied to the set of standard images "SIDBA", and using the results the filtering property is studied in details. The most important result is that the amount of information in the filtered images is greatly decreased, but sensuous degradation is very few, and hence, if the entropy filter is applied as a preprocessor of vector quantization, a new coding scheme with very low rate but few sensuous degradation will become possible. Finally, the sensuous assesment function of images is defined being based on the local entropy flow, and is evaluated for the set of standared images "SIDBA". The results show that the assesment funtion fits very well in the property of visual sensations though they are only relative values.
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Report
(1 results)
Research Products
(9 results)
