What is texture? The GLCM Texture Calculations Practical Notes More Information
Some useful references:
This list is not exhaustive! Additional comments are provided below. Kourgli and Balhadj-Aissa (1997) provide a very complete review of texture literature up to 1997, and I have not tried to reproduce it here. If you don't read French, it is still worth while for the bibliography.
There is extensive literature on the application of texture in synthetic aperture radar (SAR) images, and in applications fields such as sea ice and forestry. There is an increasing literature comparing GLCM texture measures to other approaches in terms of classification accuracy derived using them.
Akono, A.; Tonyé, E.; Nyoungui, A. N.; Rudant, J.-P. 2003. Nouvelle méthodologie d'évaluation des paramètres de texture d'ordre trois. International Journal of Remote Sensing vol. 24 no. 9 pp. 1957-1967.The only article I know of that introduces a practical way of looking at third order texture. Its utility in image analysis remains to be demonstrated since it is not in widespread use. An English abstract is provided.
Anys, H. & D-C. He 1995. Evaluation of textural and multipolarization radar features for crop classification. IEEE Transactions on Geoscience and Remote Sensing Vol. 33 no. 5 pp
Clausi, D. A. 2002. An analysis of co-occurrence texture statistics as a function of grey-level quantization. Canadian Journal of Remote Sensing vol. 28 no. 1 pp. 45-62
Coburn, C. A. and A. C. B. Roberts. 2004. A multiscale texture analysis procedure for improved forest stand classification. International Journal of Remote Sensing. vol. 25 no. 20 pp. 4287-4308.
Ferro, C. J. S. and T. A. Warner 2002. Scale and texture in digital image classification. Photogrammetric Engineering and Remote Sensing vol. 68 no. 1, pp. 51-63.
Hann, D. B.; A. M. S. Smith and A. K. Powell 2003. Classification of off-diagonal points in a co-occurrence matrix. International Journal of Remote Sensing. vol. 24 no. 9 pp. 1949-1956.
Haralick, R.M. 1979. Statistical and Structural Approaches to Texture. Proceedings of the IEEE, Vol. 67 pp.786-804.
Haralick, R.M., K. Shanmugam and I. Dinstein. 1973. Textural Features for Image Classification. IEEE Transactions on Systems, Man and Cybernetics. SMC vol. 3 no. 6 pp.610-620.
This is the "classic" GLCM texture article. It is very difficult to find in libraries. due to its azge and obscurity, I am taking the liberty of posting an incomplete (without references) scan here.
He, D-C. and L. Wang. 1990 Texture Unit, Texture Spectrum and Texture Analysis. IEEE Trans. on Geoscience and Remote Sensing, Vol. 28 no. 4 pp. 509-512
He, D.-C., L. Wang and J. Guibert. 1988. Texture Discrimination based on an optimal utilization of texture features. Pattern recognition vol. 21 no. 2 pp. 141-146.
Presents a logical method of selecting the optimal texture measures for classification of a particular image.
Jensen, J. R. 2005. Introductory Image Processing 3rd ed. Upper Saddle River, NJ: Prentice-Hall.
A basic textbook that presents texture quite exhaustively and with some examples, and an excellent bibliography.
Kourgli, A. and A.
Belhadj-Aissa. 1997. Approche structurale de génération d'images de
texture. International Journal of Remote Sensing vol. 18 no 17, pp. 3611-3627.
Pearlstine, L., K. M.
Portier and S. E. Smith. 2005. Textural discrimination of an
invasive plant, Schinus terebinthifolius, from low altitude aerial digital
imagery. Photogrammetric Engineering and Remote Sensing. 7vol. 1 no. 3 pp.
289-298.
van der Sanden, J. J. and D. H. Hoekman. 2005. Review of relationships between grey-tone co-occurrence, semivariance and autocorrelation based image texture analysis approaches. Canadian Journal of Remote Sensing vol. 38 no. 3 pp 207-213.
Potentially a very useful article in making sense of the great variety of texture measures.
Wulder, M. and B. Boots. 2001 Local Spatial Autocorrelation Characteristics of Landsat TM Imagery of a Managed Forest Area. Canadian Journal of Remote Sensing, vol. 27 no. 1 pp. 67-75