The Experts below are selected from a list of 15597 Experts worldwide ranked by ideXlab platform

W.f. Clocksin - One of the best experts on this subject based on the ideXlab platform.

  • ICIAP - Multidimensional Histogram Equalization and Modification
    2007
    Co-Authors: A.j. Mccollum, W.f. Clocksin
    Abstract:

    We describe an approach toward multidimensional Histogram Equalization for the enhancement of color and multispectral images, based on the Histogram explosion algorithm. A development from first principles is presented. We show that in, the multidimensional case, one-dimensional Histogram Equalization becomes a scalar multiplication of a vector quantity. An image noise reduction scheme is devised using a model of multispectral noise behaviour that is analogous to the behaviour of local spatial noise. Practical results are presented indicating that the method reveals subtle image features and respects the tone of the originals more consistently than earlier methods.

  • Multidimensional Histogram Equalization and Modification
    14th International Conference on Image Analysis and Processing (ICIAP 2007), 2007
    Co-Authors: A.j. Mccollum, W.f. Clocksin
    Abstract:

    We describe an approach toward multidimensional Histogram Equalization for the enhancement of color and multispectral images, based on the Histogram explosion algorithm. A development from first principles is presented. We show that in, the multidimensional case, one-dimensional Histogram Equalization becomes a scalar multiplication of a vector quantity. An image noise reduction scheme is devised using a model of multispectral noise behaviour that is analogous to the behaviour of local spatial noise. Practical results are presented indicating that the method reveals subtle image features and respects the tone of the originals more consistently than earlier methods

Seungho Hwang - One of the best experts on this subject based on the ideXlab platform.

  • an advanced contrast enhancement using partially overlapped sub block Histogram Equalization
    IEEE Transactions on Circuits and Systems for Video Technology, 2001
    Co-Authors: Seungho Hwang
    Abstract:

    An advanced Histogram-Equalization algorithm for contrast enhancement is presented. Histogram Equalization is the most popular algorithm for contrast enhancement due to its effectiveness and simplicity. It can be classified into two branches according to the transformation function used: global or local. Global Histogram Equalization is simple and fast, but its contrast-enhancement power is relatively low. Local Histogram Equalization, on the other hand, can enhance overall contrast more effectively, but the complexity of computation required is very high due to its fully overlapped sub-blocks. In this paper, a low-pass filter-type mask is used to get a nonoverlapped sub-block Histogram-Equalization function to produce the high contrast associated with local Histogram Equalization but with the simplicity of global Histogram Equalization. This mask also eliminates the blocking effect of nonoverlapped sub-block Histogram-Equalization. The low-pass filter-type mask is realized by partially overlapped sub-block Histogram-Equalization (POSHE). With the proposed method, since the sub-blocks are much less overlapped, the computation overhead is reduced by a factor of about 100 compared to that of local Histogram Equalization while still achieving high contrast. The proposed algorithm can be used for commercial purposes where high efficiency is required, such as camcorders, closed-circuit cameras, etc.

  • An advanced contrast enhancement using partially overlapped sub-block Histogram Equalization
    IEEE Transactions on Circuits and Systems for Video Technology, 2001
    Co-Authors: Joung-youn Kim, Lee-sup Kim, Seungho Hwang
    Abstract:

    An advanced Histogram-Equalization algorithm for contrast enhancement is presented. Histogram Equalization is the most popular algorithm for contrast enhancement due to its effectiveness and simplicity. It can be classified into two branches according to the transformation function used: global or local. Global Histogram Equalization is simple and fast, but its contrast-enhancement power is relatively low. Local Histogram Equalization, on the other hand, can enhance overall contrast more effectively, but the complexity of computation required is very high due to its fully overlapped sub-blocks. In this paper, a low-pass filter-type mask is used to get a nonoverlapped sub-block Histogram-Equalization function to produce the high contrast associated with local Histogram Equalization but with the simplicity of global Histogram Equalization. This mask also eliminates the blocking effect of nonoverlapped sub-block Histogram-Equalization. The low-pass filter-type mask is realized by partially overlapped sub-block Histogram-Equalization (POSHE). With the proposed method, since the sub-blocks are much less overlapped, the computation overhead is reduced by a factor of about 100 compared to that of local Histogram Equalization while still achieving high contrast. The proposed algorithm can be used for commercial purposes where high efficiency is required, such as camcorders, closed-circuit cameras, etc.

  • an advanced contrast enhancement using partially overlapped sub block Histogram Equalization
    International Symposium on Circuits and Systems, 2000
    Co-Authors: Seungho Hwang
    Abstract:

    In this paper, an advanced Histogram Equalization algorithm for contrast enhancement is presented. Histogram Equalization is the most popular algorithm for contrast enhancement due to its effectiveness and simplicity. Global Histogram Equalization is simple and fast, but its contrast enhancement power is relatively low. Local Histogram Equalization, on the other hand, can enhance overall contrast more effectively, but the computational complexity is very high due to its fully overlapped sub-blocks. For high contrast and simple calculation, a low pass filter type mask is proposed. The low pass filter type mask is realized by partially overlapped sub-block Histogram Equalization (POSHE). With the proposed method, the computation overhead is reduced by a factor of about one hundred compared to that of local Histogram Equalization while still achieving high contrast.

  • an advanced contrast enhancement using partially overlapped sub block Histogram Equalization
    International Symposium on Circuits and Systems, 2000
    Co-Authors: Joung-youn Kim, Lee-sup Kim, Seungho Hwang
    Abstract:

    In this paper, an advanced Histogram Equalization algorithm for contrast enhancement is presented. Histogram Equalization is the most popular algorithm for contrast enhancement due to its effectiveness and simplicity. Global Histogram Equalization is simple and fast, but its contrast enhancement power is relatively low. Local Histogram Equalization, on the other hand, can enhance overall contrast more effectively, but the computational complexity is very high due to its fully overlapped sub-blocks. For high contrast and simple calculation, a low pass filter type mask is proposed. The low pass filter type mask is realized by partially overlapped sub-block Histogram Equalization (POSHE). With the proposed method, the computation overhead is reduced by a factor of about one hundred compared to that of local Histogram Equalization while still achieving high contrast.

Antonio J Rubio - One of the best experts on this subject based on the ideXlab platform.

  • Histogram Equalization of speech representation for robust speech recognition
    IEEE Transactions on Speech and Audio Processing, 2005
    Co-Authors: A De La Torre, Antonio M Peinado, Jose C Segura, Jose L Perezcordoba, M C Benitez, Antonio J Rubio
    Abstract:

    This paper describes a method of compensating for nonlinear distortions in speech representation caused by noise. The method described here is based on the Histogram Equalization method often used in digital image processing. Histogram Equalization is applied to each component of the feature vector in order to improve the robustness of speech recognition systems. The paper describes how the proposed method can be applied to robust speech recognition and it is compared with other compensation techniques. The recognition experiments, including results in the AURORA II framework, demonstrate the effectiveness of Histogram Equalization when it is applied either alone or in combination with other compensation techniques.

A.j. Mccollum - One of the best experts on this subject based on the ideXlab platform.

  • ICIAP - Multidimensional Histogram Equalization and Modification
    2007
    Co-Authors: A.j. Mccollum, W.f. Clocksin
    Abstract:

    We describe an approach toward multidimensional Histogram Equalization for the enhancement of color and multispectral images, based on the Histogram explosion algorithm. A development from first principles is presented. We show that in, the multidimensional case, one-dimensional Histogram Equalization becomes a scalar multiplication of a vector quantity. An image noise reduction scheme is devised using a model of multispectral noise behaviour that is analogous to the behaviour of local spatial noise. Practical results are presented indicating that the method reveals subtle image features and respects the tone of the originals more consistently than earlier methods.

  • Multidimensional Histogram Equalization and Modification
    14th International Conference on Image Analysis and Processing (ICIAP 2007), 2007
    Co-Authors: A.j. Mccollum, W.f. Clocksin
    Abstract:

    We describe an approach toward multidimensional Histogram Equalization for the enhancement of color and multispectral images, based on the Histogram explosion algorithm. A development from first principles is presented. We show that in, the multidimensional case, one-dimensional Histogram Equalization becomes a scalar multiplication of a vector quantity. An image noise reduction scheme is devised using a model of multispectral noise behaviour that is analogous to the behaviour of local spatial noise. Practical results are presented indicating that the method reveals subtle image features and respects the tone of the originals more consistently than earlier methods

Yeong-taeg Kim - One of the best experts on this subject based on the ideXlab platform.

  • Contrast enhancement using brightness preserving bi-Histogram Equalization
    IEEE Transactions on Consumer Electronics, 1997
    Co-Authors: Yeong-taeg Kim
    Abstract:

    Histogram Equalization is widely used for contrast enhancement in a variety of applications due to its simple function and effectiveness. Examples include medical image processing and radar signal processing. One drawback of the Histogram Equalization can be found on the fact that the brightness of an image can be changed after the Histogram Equalization, which is mainly due to the flattening property of the Histogram Equalization. Thus, it is rarely utilized in consumer electronic products such as TV where preserving the original input brightness may be necessary in order not to introduce unnecessary visual deterioration. This paper proposes a novel extension of Histogram Equalization to overcome such a drawback of Histogram Equalization. The essence of the proposed algorithm is to utilize independent Histogram Equalizations separately over two subimages obtained by decomposing the input image based on its mean with a constraint that the resulting equalized subimages are bounded by each other around the input mean. It is shown mathematically that the proposed algorithm preserves the mean brightness of a given image significantly well compared to typical Histogram Equalization while enhancing the contrast and, thus, provides a natural enhancement that can be utilized in consumer electronic products.

  • ICASSP - Quantized bi-Histogram Equalization
    1997 IEEE International Conference on Acoustics Speech and Signal Processing, 1
    Co-Authors: Yeong-taeg Kim
    Abstract:

    Histogram Equalization is a widely used scheme for contrast enhancement in a variety of applications due to its simple function and effectiveness. One possible drawback of the Histogram Equalization is that it can change the mean brightness of an image significantly as a consequence of Histogram flattening. Clearly, this is not a desirable property when preserving the original mean brightness of a given image is necessary. As an effort to overcome such drawback for extending the applications of the Histogram Equalization in consumer electronic products, bi-Histogram Equalization has been proposed by the author which is capable of preserving the mean brightness of an image while it performs contrast enhancement. The essence of the bi-Histogram Equalization is to utilize independent Histogram Equalizations separately over two subimages obtained by decomposing the input image based on its mean. A simplified version of the bi-Histogram Equalization is proposed, which is referred to as the quantized bi-Histogram Equalization. The proposed algorithm provides a much simpler hardware (H/W) structure than the bi-Histogram Equalization since it is based on the cumulative density function of a quantized image. Thus, the realization of bi-Histogram Equalization in H/W is feasible, which leads to versatile applications in the field of consumer electronics.