Abstract
Computed Tomography (CT) images have a high dynamic range, which makes visualization challenging. Histogram equalization methods either use spatially invariant weights or limited kernel size due to the complexity of pairwise contribution calculation. We present a weighted histogram equalization-based tone mapping algorithm which utilizes Fast Fourier Transform for distance-dependent contribution calculation and distance-based weights. The weights follow power-law without distance-based cut-off. The resulting images have good local contrast without noticeable artefacts. The results are compared to eight popular tone mapping operators.
Highlights
Global and local contrasts are often imperfect in images
Computed Tomography (CT) images have low soft tissue contrast, a relatively high noise level compared to magnetic resonance imaging (MRI), and they have a high dynamic range [4]
The aim of this paper is to develop a local tone mapping operator which lies somewhere between global and local histogram equalization and combines their advantages and avoids their shortcomings
Summary
Global and local contrasts are often imperfect in images. The available dynamic range of the display is either not utilized, or, on the contrary, the range is wider than the low dynamic range display.Medical images, Computed Tomography (CT) images, are challenging to visualize.First, artefacts could lead to inferior diagnostic performance [1]. Global and local contrasts are often imperfect in images. The available dynamic range of the display is either not utilized, or, on the contrary, the range is wider than the low dynamic range display. Computed Tomography (CT) images, are challenging to visualize. Artefacts could lead to inferior diagnostic performance [1]. A lack of good local contrast could limit diagnostic performance; local contrast enhancement can improve diagnostic efficiency [2]. Significantly reduce interpretation times [3]. CT images have low soft tissue contrast, a relatively high noise level compared to magnetic resonance imaging (MRI), and they have a high dynamic range (approximately 12 bits) [4]
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