Use of Fuzzy Edge Image in Block Truncation Coding for Image Compression
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Use of Fuzzy Edge Image in Block Truncation Coding for Image Compression

Authors: Amarunnishad T.M., Govindan V.K., Abraham T. Mathew

Abstract:

An image compression method has been developed using fuzzy edge image utilizing the basic Block Truncation Coding (BTC) algorithm. The fuzzy edge image has been validated with classical edge detectors on the basis of the results of the well-known Canny edge detector prior to applying to the proposed method. The bit plane generated by the conventional BTC method is replaced with the fuzzy bit plane generated by the logical OR operation between the fuzzy edge image and the corresponding conventional BTC bit plane. The input image is encoded with the block mean and standard deviation and the fuzzy bit plane. The proposed method has been tested with test images of 8 bits/pixel and size 512×512 and found to be superior with better Peak Signal to Noise Ratio (PSNR) when compared to the conventional BTC, and adaptive bit plane selection BTC (ABTC) methods. The raggedness and jagged appearance, and the ringing artifacts at sharp edges are greatly reduced in reconstructed images by the proposed method with the fuzzy bit plane.

Keywords: Image compression, Edge detection, Ground truth image, Peak signal to noise ratio

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1084788

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References:


[1] Graham D. Image Transmission by Two-dimensional Contour Coding. Proc IEEE 1967; 55(3): 336-346.
[2] Kocher M, Kunt M. Image Data Compression by Contour Texture Modeling. SPIE Int Conf on the Applications of Digital Image Processing, Geneva, Switzerland, April 1983: 131-139.
[3] Carlsson S. Sketch based Coding of Grey level Images. Signal Processing 1988; 15: 57-83.
[4] Cheng SC, Tsai WH. Image Compression by Moment-Preserving Edge Detection. Pattern Recognition1994; 27(11): 1439-1449.
[5] Desai UY, Mizuki MM, Masaki I, Horn BKP. Edge and Mean Based Compression. MIT Artificial Intelligence Lab A I Memo No.1584, November 1996.
[6] Aggoun A, Mabrouk AE. Image Compression Algorithm using Local Edge Detection. IEEE COMSOC/EURASIP First International Workshop on Wireless Image/Video Communications, September 1996.
[7] Han WY, Lin JC. Edge Detection and Edge Preserved Compression for Error-Diffused Images. Comput and Graphics 1997; 21(6): 757-767.
[8] Neves SR, Mendonca GV. Image Coding Based on Edges and Textures via Wavelet Transform. Proc of the Int Conf on Acoustics, Speech, and Signal processing 1998; 5: 2689-2692.
[9] Ryu H, Miyanaga Y, Tochinai K. Self-Organized Edge Detection for Image Compression. IEEE Int Symp on Circuits and Systems, Geneva, Switzerland, May 2000: 625-628.
[10] Yang CK, Tsai WH. Improving Block Truncation Coding by Line and Edge Information and Adaptive Bit Plane Selection for Gray-Scale Image Compression. Pattern Recognition Letters 1995; 16: 67-75.
[11] Delp EJ, Mitchell OR. Image Compression using Block Truncation Coding. IEEE Transactions on Communications 1979; 27(9): 1335- 1342.
[12] Chan KW, Chan KL. Optimization of Multi-Level Block truncation Coding. Signal Processing: Image Communication 2001; 16: 445-459.
[13] Franti P, Nevalainen O, Kaukoranta T. Compression of Digital Images by Block Truncation Coding: A Survey, The Computer Journal, Vol. 37, No. 4, 1994.
[14] Mitchell HB, Zilverberg N, Avraham M. A Comparison of Different Block Truncation Coding Algorithms for Image Compression. Signal Processing: Image Communication 1994; 6: 77-82.
[15] Liang LR, Looney CG. Competitive Fuzzy Edge Detection. Applied Soft Computing 2003; 3: 123-137.
[16] Sonka M, Hlavac V, Boyle R. Image Processing, Analysis, and machine Vision (2nd Edn.), Thomson Brooks/Cole; 1999.
[17] Kuo YH, Lee CS, Liu CC. A New Fuzzy Edge Detection Method for Image Enhancement. Sixth IEEE Int Conf on Fuzzy Systems 1997; 2: 1069-1074.
[18] Tizhoosh HR. Fast Fuzzy Edge Detection. Proceedings of the North American Fuzzy Information Processing Society (IEEE - NAFIPS), June 2002: 239-242.
[19] Prieto MS, Allen AR. A Similarity Metric for Edge Images. IEEE Trans on Pattern Analysis and Machine Intelligence 2003; 25(10): 1265-1273.