A nonlinear edge detection technique
01 May 1970-Vol. 58, Iss: 5, pp 814-816
TL;DR: Using a product of differences of averages taken over pairs of adjacent nonoverlapping neighborhoods tends to yield sharply localized edges.
Abstract: Major "edges" in a noisy signal or picture can be detected by subtracting averages taken over pairs of adjacent nonoverlapping neighborhoods, but this method does not locate the edges precisely. It has been found that using a product of such differences of averages tends to yield sharply localized edges.
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TL;DR: Simple sets of parallel operations are described which can be used to detect texture edges, "spots," and "streaks" in digitized pictures and it is shown that a composite output is constructed in which edges between differently textured regions are detected, and isolated objects are also detected, but the objects composing the textures are ignored.
Abstract: Simple sets of parallel operations are described which can be used to detect texture edges, "spots," and "streaks" in digitized pictures. It is shown that, by comparing the outputs of the operations corresponding to (e.g.,) edges of different sizes, one can construct a composite output in which edges between differently textured regions are detected, and isolated objects are also detected, but the objects composing the textures are ignored. Relationships between this class of picture processing operations and the Gestalt psychologists' laws of pictorial pattern organization are also discussed.
811 citations
Cites background from "A nonlinear edge detection techniqu..."
...Fig. 6 .Conspicuous edgedetection results foraTIROScloudcover picture....
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...Someadditional two-dimensional results, foraTIROScloud cover picture, areshowninFig. 6 .Theseresults usehorizontal andvertical detectors only; theoutput ateachpoint isthe larger ofthebest horizontal andbest vertical detectors....
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...Results for(a)-(c) areshownin(d)-(f). In(g), points of(f) with values below 6 ...
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TL;DR: A spatially selective noise filtration technique based on the direct spatial correlation of the wavelet transform at several adjacent scales is introduced and can reduce noise contents in signals and images by more than 80% while maintaining at least 80% of the value of the gradient at most edges.
Abstract: Wavelet transforms are multiresolution decompositions that can be used to analyze signals and images They describe a signal by the power at each scale and position Edges can be located very effectively in the wavelet transform domain A spatially selective noise filtration technique based on the direct spatial correlation of the wavelet transform at several adjacent scales is introduced A high correlation is used to infer that there is a significant feature at the position that should be passed through the filter The authors have tested the technique on simulated signals, phantom images, and real MR images It is found that the technique can reduce noise contents in signals and images by more than 80% while maintaining at least 80% of the value of the gradient at most edges The authors did not observe any Gibbs' ringing or significant resolution loss on the filtered images Artifacts that arose from the filtration are very small and local The noise filtration technique is quite robust There are many possible extensions of the technique The authors see its applications in spatially dependent noise filtration, edge detection and enhancement, image restoration, and motion artifact removal They have compared the performance of the technique to that of the Weiner filter and found it to be superior >
793 citations
TL;DR: The algorithm appears to be more effective than previous techniques for two key reasons: 1) the gradient orientation is used as the initial organizing criterion prior to the extraction of straight lines, and 2) the global context of the intensity variations associated with a straight line is determined prior to any local decisions about participating edge elements.
Abstract: This paper presents a new approach to the extraction of straight lines in intensity images. Pixels are grouped into line-support regions of similar gradient orientation, and then the structure of the associated intensity surface is used to determine the location and properties of the edge. The resulting regions and extracted edge parameters form a low-level representation of the intensity variations in the image that can be used for a variety of purposes. The algorithm appears to be more effective than previous techniques for two key reasons: 1) the gradient orientation (rather than gradient magnitude) is used as the initial organizing criterion prior to the extraction of straight lines, and 2) the global context of the intensity variations associated with a straight line is determined prior to any local decisions about participating edge elements.
742 citations
TL;DR: The technique of scale multiplication is analyzed in the framework of Canny edge detection and the detection and localization criteria of the scale multiplication are derived, finding that at a small loss in the detection criterion, the localization criterion can be much improved by scale multiplication.
Abstract: The technique of scale multiplication is analyzed in the framework of Canny edge detection. A scale multiplication function is defined as the product of the responses of the detection filter at two scales. Edge maps are constructed as the local maxima by thresholding the scale multiplication results. The detection and localization criteria of the scale multiplication are derived. At a small loss in the detection criterion, the localization criterion can be much improved by scale multiplication. The product of the two criteria for scale multiplication is greater than that for a single scale, which leads to better edge detection performance. Experimental results are presented.
515 citations
TL;DR: A variety of edge detectors are described and their performance is evaluated in terms of some known performance measures to categorize the different edge detection schemes and to better understand the usefulness and limitations of the performance measures used.
332 citations