Pixel Classification Based on Gray Level and Local ``Busyness''

Dondes, P. A.; Rosenfeld, Azriel

doi:10.1109/tpami.1982.4767200

Cited by 18 publications

(4 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Note that the probability p l in Equation (17) is computed for all pixels at the same gray level, rather than for a single pixel in Equation (14). In the literature, the parameter m l is commonly referred to as the busyness or activity of the gray level l [37,45].…”

Section: Entropies Based On the Gray-level Variance Of Neighborhoods mentioning

confidence: 99%

Thermodynamics-Based Evaluation of Various Improved Shannon Entropies for Configurational Information of Gray-Level Images

Gao

Zhang

2018

Entropy

View full text Add to dashboard Cite

Abstract:The quality of an image affects its utility and image quality assessment has been a hot research topic for many years. One widely used measure for image quality assessment is Shannon entropy, which has a well-established information-theoretic basis. The value of this entropy can be interpreted as the amount of information. However, Shannon entropy is badly adapted to information measurement in images, because it captures only the compositional information of an image and ignores the configurational aspect. To fix this problem, improved Shannon entropies have been actively proposed in the last few decades, but a thorough evaluation of their performance is still lacking. This study presents such an evaluation, involving twenty-three improved Shannon entropies based on various tools such as gray-level co-occurrence matrices and local binary patterns. For the evaluation, we proposed: (a) a strategy to generate testing (gray-level) images by simulating the mixing of ideal gases in thermodynamics; (b) three criteria consisting of validity, reliability, and ability to capture configurational disorder; and (c) three measures to assess the fulfillment of each criterion. The evaluation results show only the improved entropies based on local binary patterns are invalid for use in quantifying the configurational information of images, and the best variant of Shannon entropy in terms of reliability and ability is the one based on the average distance between same/different-value pixels. These conclusions are theoretically important in setting a direction for the future research on improving entropy and are practically useful in selecting an effective entropy for various image processing applications.

show abstract

Section: Entropies Based On the Gray-level Variance Of Neighborhoods mentioning

confidence: 99%

Thermodynamics-Based Evaluation of Various Improved Shannon Entropies for Configurational Information of Gray-Level Images

Gao

Zhang

2018

Entropy

View full text Add to dashboard Cite

show abstract

“…It helps to find the difference between regions in an image. Busyness of a pixel [x, y] in a 3 × 3 neighborhood matrix is the average of absolute grayness differences of all pairs of twelve adjacent pixels in the neighborhood [10]. The average difference is high in the busy neighborhood where many adjacent pair differ, but it should be low in neighborhood containing vertical or horizontal edges.…”

Section: Busynessmentioning

confidence: 99%

A New Image Edge Detection Method using Quality-based Clustering

Neupane¹,

Aung²,

Woon³

2012

Visualization, Imaging and Image Processing / 783: Modelling and Simulation / 784: Wireless Communications

View full text Add to dashboard Cite

Due to the various limitations of existing edge detection methods, finding better algorithms for edge detection is still an active area of research. Many edge detection approaches have been proposed in the literature but in most cases, the basic approach is to search for abrupt change in color, intensity or other properties. Unfortunately, in many cases, images are corrupted with different types of noise which might cause sharp changes in some of these properties. In this paper, we propose a new method for edge detection which uses k-means clustering, and where different properties of image pixels were used as features. We analyze the quality of the different clusterings obtained using different k values (i.e., the predefined number of clusters) in order to choose the best number of clusters. The advantage of this approach is that it shows higher noise resistance compared to existing approaches. The performance of our method is compared against those of other methods by using images corrupted with various levels of "salt and pepper" and Gaussian noise. It is observed that the proposed method displayed superior noise resilience.

show abstract

“…Here, HTV, VTV, DTV, and ADTV denote the variations along the horizontal, vertical, diagonal, and antidiagonal directions, respectively. They are defined as follows ͑see Experimental evidence 12 indicates that the technique for measuring the MTV can detect not only the existence of the edges, but also the orientations of the edges. According to the orientation of edges, we have four kinds of edgecodebooks, namely, horizontal, vertical, diagonal, and antidiagonal.…”

Section: Habtc-vq (The Optional Version With Vq)mentioning

confidence: 99%

Hybrid adaptive block truncation coding for image compression

Yang

Lin

1997

Opt. Eng

View full text Add to dashboard Cite

A hybrid adaptive block truncation coding (HABTC) method is presented to improve block truncation coding (BTC)-related compression methods for gray-level images. The basic idea behind the method is to use various coding schemes to take advantage of local image characteristics. A simple linear interpolation coding scheme and a very basic predictive coding scheme are used to improve the compression ratio of the homogeneous area of the image. Moreover, a four-level BTC, whose thresholds are obtained using a radius-weighted mean (RWM), is applied to encode the inhomogeneous area. The bits per pixel/peak SNR (bpp/PSNR) values listed in many other BTC-related papers are cited and compared with ours. It is found that reasonable compression ratio is obtained by the proposed HABTC method and the visual quality of the decoded images is also acceptable. © 1997 Society of Photo-Optical Instrumentation Engineers. [S0091-3286(97)00104-9] Subject terms: image compression; hybrid adaptive block truncation coding; linear interpolation coding; predictive coding; radius weighted mean; vector quantization.

show abstract

Pixel Classification Based on Gray Level and Local ``Busyness''

Cited by 18 publications

References 5 publications

Thermodynamics-Based Evaluation of Various Improved Shannon Entropies for Configurational Information of Gray-Level Images

Thermodynamics-Based Evaluation of Various Improved Shannon Entropies for Configurational Information of Gray-Level Images

A New Image Edge Detection Method using Quality-based Clustering

Hybrid adaptive block truncation coding for image compression

Contact Info

Product

Resources

About