A Framework for Low Level Feature Extraction

The paper presents a framework for extracting low level features. Its main goal is to explicitely exploit the information content of the image as far as possible. This leads to new techniques for deriving image parameters, to either the elimination or the elucidation of ”buttons”, like thresholds, and to interpretable quality measures for the results, which may be used in subsequent steps. Feature extraction is based on local statistics of the image function. Methods are available for blind estimation of a signal dependent noise variance, for feature preserving restoration, for feature detection and classification, and for the location of general edges and points. Their favorable scale space properties are discussed.

[1]  Athanasios Papoulis,et al.  Probability, Random Variables and Stochastic Processes , 1965 .

[2]  G. Granlund.  In search of a general picture processing operator , 1978 .

[3]  D. McClure.  Image models in pattern theory , 1980 .

[4]  Hans Knutsson,et al.  Texture Analysis Using Two-Dimensional Quadrature Filters , 1983 .

[5]  V. Berzins.  Accuracy of laplacian edge detectors , 1984 .

[6]  Andrew P. Witkin,et al.  Analyzing Oriented Patterns , 1985, IJCAI.

[7]  Tomaso A. Poggio,et al.  On Edge Detection , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[8]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[9]  David J. Heeger,et al.  Optical flow from spatialtemporal filters , 1987 .

[10]  U. Grenander.  Advances in Pattern Theory , 1989 .

[11]  Azriel Rosenfeld,et al.  A Fast Parallel Algorithm for Blind Estimation of Noise Variance , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[12]  J. Bigun.  A structure feature for some image processing applications based on spiral functions , 1990 .

[13]  Uwe Weidner,et al.  Informationserhaltende Filterung digitaler Bilder und ihre Bewertung , 1991, DAGM-Symposium.

[14]  Tai Sing Lee,et al.  Texture Segmentation by Minimizing Vector-Valued Energy Functionals: The Coupled-Membrane Model , 1992, ECCV.

[15]  Rüdiger von der Heydt,et al.  Detection of General Edges and Keypoints , 1992, ECCV.

[16]  G. Granlund.  Image Sequence Analysis , 1993, DAGM-Symposium.

[17]  Wolfgang Förstner.  FEATURE EXTRACTION IN DIGITAL PHOTOGRAMMETRY , 1993 .

[18]  Uwe Weidner,et al.  Parameterfree Information-Preserving Surface Restoration , 1994, ECCV.