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Image Representation with Gabor Wavelets and Its Applications

Elsevier Science & Technology
DOI: 10.1016/s1076-5670(08)70093-4
  • Biology
  • Physics


Publisher Summary The field of application of Gabor wavelets (GWs) and similar schemes of image representation is huge and continuously increasing. They are highly useful in almost every problem of image processing, coding, enhancement and analysis, and low to mid-level vision, including modeling biological vision. Moreover, multiscale and wavelet representations have provided important breakthroughs in image understanding and analysis. Furthermore, Gabor functions are a widely used tool for visual testing in psychophysical and physiological studies. Gaussian envelopes are very common in grating stimuli to measure contrast sensitivity, to study shape, texture, motion perception, or modeling brightness perception. All these facts suggest that GWs are especially suitable for building general-purpose environments for image processing, analysis, and artificial vision systems. The chapter presents the classification of the most relevant applications in three groups: (1) modeling of early processing in the human visual system in, (2) applications to image coding, enhancement, and reconstruction, (3) and applications to image analysis and machine vision. Prior to these applications, the chapter reviews the main conjoint image representations, and then specifically discusses Gabor representations.

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