Abstract
This study develops an approach to improve the quality of infrared (IR) images of vein-patterns, which usually have noise, low contrast, low brightness and small objects of interest, thus requiring preprocessing to improve their quality. The main characteristics of the proposed approach are that no prior knowledge about the IR image is necessary and no parameters must be preset. Two main goals are sought: impulse noise reduction and adaptive contrast enhancement technologies. In our study, a fast median-based filter (FMBF) is developed as a noise reduction method. It is based on an IR imaging mechanism to detect the noisy pixels and on a modified median-based filter to remove the noisy pixels in IR images. FMBF has the advantage of a low computation load. In addition, FMBF can retain reasonably good edges and texture information when the size of the filter window increases. The most important advantage is that the peak signal-to-noise ratio (PSNR) caused by FMBF is higher than the PSNR caused by the median filter. A hybrid cumulative histogram equalization (HCHE) is proposed for adaptive contrast enhancement. HCHE can automatically generate a hybrid cumulative histogram (HCH) based on two different pieces of information about the image histogram. HCHE can improve the enhancement effect on hot objects rather than background. The experimental results are addressed and demonstrate that the proposed approach is feasible for use as an effective and adaptive process for enhancing the quality of IR vein-pattern images.
Highlights
Because the cost of IR cameras has declined in recent years, especially those that are not cooled, the number of applications based on IR images captured by un-cooled IR cameras has increased substantially
In order to remedy this shortcoming of histogram equalization (HE), this paper proposes a hybrid cumulative histogram equalization (HCHE), whose main property is the use of two different enhancement effects on hot objects and backgrounds: a large effect on hot objects and a small effect on backgrounds
This paper presents an approach to improve the quality of IR images of vein-patterns by using the fast median-based filter (FMBF) and HCHE with hybrid cumulative histogram (HCH)
Summary
Because the cost of IR cameras has declined in recent years, especially those that are not cooled, the number of applications based on IR images captured by un-cooled IR cameras has increased substantially. A FMBF to IR images based on an IR imaging mechanism to detect impulse noise and that is median-based to remove impulse noise with low computational load is developed It can be performed without any prior knowledge about the IR image impulse noise, and no parameters must be preset. To enhance the IR images automatically, we have developed a novel adaptive contrast enhancement approach, which automatically generates a hybrid cumulative histogram (HCH) based on two different pieces of information about the image histogram. It consists of four main parts, which are noise detection, noise removal, selecting an adaptive threshold and generating a hybrid cumulative histogram.
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