International audienceThis article addresses the problem of histogram matching in the context of medical image processing. Such a problem occurs while comparing two images of the same object, where intensity differences are due to different acquisition conditions. This can be compensated by histogram matching or equalization. To achieve this, we based our method on windowing techniques. This allows to match implicitly continuous probability density functions, yielding more robust results than the methods issued from discrete histograms
Histogram equalization (HE), an image enhancement method, is widely used in many aspects of image pr...
Image contrast enhancement techniques can be used in various image processing applications. There ar...
Histogram equalization is a nonlinear technique for adjusting the contrast of an image using its his...
Image contrast enhancement is a fundamental pre-processing stage in applications requiring image pro...
Image contrast enhancement is a fundamental and important pre-processing stage in the application of...
Intensity standardization is an important preprocessing step in automatedanalysis of MRI. A popular ...
[[abstract]]Histogram equalization (HE) is a widely used contrast enhancement (CE) method in image p...
Abstract- Image enhancement is one of the most important issues in image processing. Various enhance...
Four algorithms that modify the histogram equalization algorithm, and extend its capability to a lar...
An analysis of the local histogram equalization algorithm is presented. An adaptation of the algorit...
Abstract- Histogram equalization is a technique of improving the global contrast of an image by adju...
Abstract-Adaptive histogram equalization (AHE), a method of con-trast enhancement which is sensitive...
Abstract: Histogram equalization is a well-known image contrast enhancement method. In practice, how...
Medical images form a part of real world images which come with a wide variety of contrast and brigh...
Intensity normalization is important in quantitative image analysis, especially when extracting feat...
Histogram equalization (HE), an image enhancement method, is widely used in many aspects of image pr...
Image contrast enhancement techniques can be used in various image processing applications. There ar...
Histogram equalization is a nonlinear technique for adjusting the contrast of an image using its his...
Image contrast enhancement is a fundamental pre-processing stage in applications requiring image pro...
Image contrast enhancement is a fundamental and important pre-processing stage in the application of...
Intensity standardization is an important preprocessing step in automatedanalysis of MRI. A popular ...
[[abstract]]Histogram equalization (HE) is a widely used contrast enhancement (CE) method in image p...
Abstract- Image enhancement is one of the most important issues in image processing. Various enhance...
Four algorithms that modify the histogram equalization algorithm, and extend its capability to a lar...
An analysis of the local histogram equalization algorithm is presented. An adaptation of the algorit...
Abstract- Histogram equalization is a technique of improving the global contrast of an image by adju...
Abstract-Adaptive histogram equalization (AHE), a method of con-trast enhancement which is sensitive...
Abstract: Histogram equalization is a well-known image contrast enhancement method. In practice, how...
Medical images form a part of real world images which come with a wide variety of contrast and brigh...
Intensity normalization is important in quantitative image analysis, especially when extracting feat...
Histogram equalization (HE), an image enhancement method, is widely used in many aspects of image pr...
Image contrast enhancement techniques can be used in various image processing applications. There ar...
Histogram equalization is a nonlinear technique for adjusting the contrast of an image using its his...