Image classification

The computer aided classification of the remotely sensed data is based on the concept that a pixel is characterized by its spectral signatures, which vary in different wave bands. The spectral signatures of themes are assigned a gray level or color which relates the Dn values to thematic information. The information extraction process which analyzes the spectral signatures and assigns the pixel to thematic categories based on similarity of Dn values is referred to as classification. There are two types of classification  

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Wolkenstein M, Hutter H, Nikolov SG, Grasserbauer M (1997a) Improvement of SIMS image classification by means of de-noising. Fresenius J Anal Chem 357 783... 

Harsanyi, J.C. and Chang, C.-I., Hyperspectral image classification and dimensionality reduction an orthogonal subspace projection approach, IEEE Trans. Geosci. Rem. Sens., 32, 779, 1994. 

Molz, R. F, Engel, P. M., Moraes, F. G., Torres, L., and Robert, M. "A Fast Prototyping Neural Network Model for Image Classification." In Proceedings of the XV Conference on Design of Circuit and Integrated Systems (DCIS), 1 (2000) 836-41. 

M. Wolkenstein, H. Hutter, S.G. Nikolov and M. Grasserbauer, Improvement ol SIMS Image Classification by Means of Wavelet Denoising. Fresenius Journal oj Analytical Chemistry. 357 (1997b), 783-788. 

A further investigation in the general framework of multiscale methods [12] and scale-space theory [31,32] may be classification at different scales. If for some types of images classification gives the same or very similar results at several scales, then it may be performed on smaller, smoothed copies of the... 

S. Livens, P. Scheunders, G. van de Wouwer, D. van Dyck, H. Smets, J. Winkel-mans and W. Bogaerts, A Texture Analysis Approach to Corrosion Image Classification, Microsc., Microanal., Microstrut t.. 7 (2) (1996), 143-152. 

Multisource image classification II An empirical comparison of evidential reasoning and neural network approaches. Canadian Journal of Remote Sensing, 12, 277-302. 

Table 2.1. Magnetic resonance (MR) imaging classification of cavernous angioma (Zabramski et al. 1994)...

The categories of interest must be carefully selected and defined to successfully perform digital image classification. It is essential to realize the fundamental difference between the information classes (defined by the analyst) and spectral classes (inherent of sensor). The major point of difference between various classification schemes is their emphasis and ability to convert spectral classes into information classes of remote sensing data. 

The second step involves the apphcation of a non-linear parabolic equation [72] to the two selected quickbird scenes. This equation allows selective enhancement and smoothing in addition to simultaneously preventing the blurring of the edges. The processing is quite effective for image classification in urban areas. The equation is stated as ... 

Ramirez J, Gorriz JM, Segovia F, Chaves R, Salas-Gonzalez D, Lopez M et al. Computer aided diagnosis system for the Alzheimer s disease based on partial least squares and random forest SPECT image classification. Neuroscience Letters. 2010 472(2) 99-103. 

Improvement of SIMS Image Classification by Means of Wavelet De-Noising. 

Mazhar B.Tayel, Mohamed E.El-Bouridy, ECG images classification using features extraction based on wavelet transformation and neu-ralnetwOTk, AIML 06 International Conference, 13-15 June 2006, Sharm El Sheikh, Egypt, 105-107... 

After image processing, the texture features and morphological features of the tumor were analyzed for image classification [1, 3]. Moreover, the statistically effective features were selected by the independent t-test and served as inputs... 

The sensitivity of the CAD system was effectively increased by using more reference neurons to classify the pancreatic tumor images. The area of a pancreatic tumor seemed to be the most important morphological feature for image classification, as shown in Figure 8. A benign pancreatic tumor usually had a smaller area and a smoother contour than a malignant one. 

Keywords Retinal Vessel Detection Preprocessing methods Medical image classification Diabetic retinopathy 2D Gabor wavelets Matched filters... 

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