色彩影像初階校正與縮放技術研究

蔡孟達

doi:10.6840/cycu200500362

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色彩影像初階校正與縮放技術研究

Color Image Preliminary Calibration and Resizing Technique

蔡孟達 , Masters　　Advisor：張元翔　　

繁體中文 DOI： 10.6840/cycu200500362

色彩影像；色彩校正；色彩影像縮放；內插法技術； calibration ； interpolation technique ； color images ； image resizing

Abstract │ Reference (22) │ Times Cited (3) │ Altmetrics

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With the advance of imaging and information techniques, digital images are popular everywhere. The color of image has also been developed from achromatic to chromatic. So, color imaging device (ex. scanner) has become more and more popular. Except for efficiency, consumers respect color quality. It is very important that digital color data represent original color. Calibration is a technique of correcting color characteristics. In general, calibration process is not tedious. So, general users can not easily calibrate themselves. This thesis tried to develop one simple calibration process. It could help users calibrate themselves and achieve certain degree of calibration. Using the property of linear distribution of standard color chart, we fixed the non-linear response error during scanning process. Experimental results show that the process we proposed achieved preliminary success. However, for better results, more research effort is desired.
    Basic technique of image processing (e.g. resizing, segmentation etc.) is usually the basic operator of medical image and digital multimedia. If the results of fundamental processing are performed badly, this could cause distortion such that the follow-up step will be processing wrong data. This thesis is to study the color image resizing. Image resizing was generally processed by interpolation. The conventional interpolation included: Nearest Neighbor Interpolation, Bilinear Interpolation, and Bicubic Interpolation. The conventional interpolation could not achieve high quality of image resizing. This thesis is an attempt to overcome the deficiency of conventional methods and to study another method, namely oblique projection of B-Spline interpolation. Both subjective and objective (Signal to Noise Ratio) methods are used to estimate the quality of resized images. Experimental results show that the oblique projection of B-Spline interpolation has achieved best results. However, the oblique projection of B-Spline interpolation was not the most efficient image resizing processing method.

Reference ( 22 ) 〈TOP〉

[1] Vrhel M. J., and Trussel H. J., "The Mathematics of Color Calibration", IEEE, 1998
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[2] T. Uchiyama and M. A. Arbib, “Color image segmentation using competitive learning”, IEEE Trans. on Pattern Anal. Machine Intell., Vol. 16, pp. 1197-1206, 1994.
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[3] E. Littmann and H. Ritter, “Adaptive color segmentation – A comparison of neural and statistical methods,” IEEE Trans. on Neural Networks, Vol. 8, Jan. 1997.
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[4] H. -D. Cheng, Y. Sun, “A hierarchical approach to color image segmentation using homogeneity,” IEEE Trans. on Image Processing, Vol. 9, No. 12, pp. 2071-2082, 2000.
連結：
[5] N. Vandenbroucke, L. Macaire, J. -G. Postaire, “Color image segmentation by pixel classification in an adapted hybrid color space. Application to soccer image analysis,” Computer Vision and Image Understanding, Vol. 90, pp. 190-216, 2003.
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