What is scale-space theory?

For an uncommitted vision system, the scale-space theory states that the natural operations of perform in a visual front-end are convolutions with Gaussian kernels and their derivatives at di erent scales. The output from these operations can then, in turn, be used as input to a large number of other visual modules.

What is scale-space in image processing?

The size (scale) of the objects is dependent on the distance from the camera. A visual system should be prepared to ‘see’ objects at all possible sizes. Smoothing an image at all possible scales s>0 leads to what is called a scale-space.

What is scale-space filtering?

Scale-space filtering is a method that describes signals qualitatively, managing the ambiguity of scale in an organized and natural way. The signal is first expanded by convolution with gaussian masks over a continuum of sizes.

What is Gaussian scale?

Gaussian scale-space is one of the best understood multi-resolution techniques available to the computer vision and image analysis community. It is the purpose of this book to guide the reader through some of its main aspects.

Is there a link between scale space and biological vision?

There is a close link between scale-space theory and biological vision. Many scale-space operations show a high degree of similarity with receptive field profiles recorded from the mammalian retina and the first stages in the visual cortex.

When to use multiple scales in computer vision?

For a computer vision system analysing an unknown scene, there is no way to know a priori what scales are appropriate for describing the interesting structures in the image data. Hence, the only reasonable approach is to consider descriptions at multiple scales in order to be able to capture the unknown scale variations that may occur.

Which is the best description of scale space?

Scale space. Scale-space theory is a framework for multi-scale signal representation developed by the computer vision, image processing and signal processing communities with complementary motivations from physics and biological vision. It is a formal theory for handling image structures at different scales,…

How is scale space used in image processing?

Scale-space operations have also been frequently used for expressing coarse-to-fine methods, in particular for tasks such as image matching and for multi-scale image segmentation . The theory presented so far describes a well-founded framework for representing image structures at multiple scales.