The proposed method is a new approach for enhancing grayscale images, when the images are map to quaternion space, and then, the quaternion based enhancement technique is used. Namely, the quaternion alpha-rooting method to enhance the so generated “quaternion” image. Currently, there are only very limited techniques to convert a grayscale image to color image, and in this article we propose a novel conversion technique which helps in easily converting a grayscale image to a color or quaternion image. In addition to that, we describe the quaternion alpha-rooting method of quaternion image enhancement. Quaternion approach of enhancement allows for processing the multi-signaled image as a single unit. The fast algorithm of quaternion discrete Fourier transforms makes the implementation of the enhancement method practically possible and effective. The results of image enhancement by the proposed method and comparison with the traditional alpha-rooting of grayscale images are described. The metric used to assess the quality of enhancement shows good values for the results of the proposed enhancement. One of the enhancement metrics is the contrast-based metric referred to as the enhancement measure estimation (EME). Other metrics used to assess the quality of the enhanced images are signal-to-noise ratio (SNR), mean-square-root error (MSRE).
KEYWORDS: Image enhancement, 3D image enhancement, Medical imaging, 3D image processing, RGB color model, Visualization, Eye models, Blood, Image processing
The proposed method is a novel image enhancement for color medical images. In this method, the 3-D medical image is transformed first to the 2-D grayscale image and then the enhancement algorithms, either in frequency domain or spatial domain, are applied to the grayscale image. This paper describes the enhancement effects on the medical images by the proposed transformation model and then the enhancement by the alpha-rooting method, for the frequency domain algorithm, and the histogram equalization, for the spatial domain enhancement algorithm. The enhancement is quantitatively measured with respect to the metric which is called the color enhancement measure estimation (CEME). The proposed method is showing good CEME values as compared to the original images.
2-D quaternion discrete Fourier transform (2-D QDFT) is the Fourier transform applied to color images when the color images are considered in the quaternion space. The quaternion numbers are four dimensional hyper-complex numbers. Quaternion representation of color image allows us to see the color of the image as a single unit. In quaternion approach of color image enhancement, each color is seen as a vector. This permits us to see the merging effect of the color due to the combination of the primary colors. The color images are used to be processed by applying the respective algorithm onto each channels separately, and then, composing the color image from the processed channels. In this article, the alpha-rooting and zonal alpha-rooting methods are used with the 2-D QDFT. In the alpha-rooting method, the alpha-root of the transformed frequency values of the 2-D QDFT are determined before taking the inverse transform. In the zonal alpha-rooting method, the frequency spectrum of the 2-D QDFT is divided by different zones and the alpha-rooting is applied with different alpha values for different zones. The optimization of the choice of alpha values is done with the genetic algorithm. The visual perception of 3-D medical images is increased by changing the reference gray line.
The LIDAR equation contains four unknown variables in a two-component atmosphere where the effects
caused by both molecules and aerosols have to be considered. The inversion of LIDAR returns to retrieve aerosol
extinction profiles, thus, calls for some functional relationship to be assumed between these two. The Klett's method,
assumes a functional relationship between the extinction and backscatter. In this paper, we apply a different technique,
called the optical depth solution, where we made use of the total optical depth or transmittance of the atmosphere along
the LIDAR-measurement range. This method provides a stable solution to the LIDAR equation. In this study, we apply
this technique to the data obtained using a micro pulse LIDAR (MPL, model 1000, Science and Engineering Services
Inc) to retrieve the vertical distribution of aerosol extinction coefficient. The LIDAR is equipped with Nd-YLF laser at
an operating wavelength of 523.5 nm and the data were collected over Bangalore. The LIDAR data are analyzed to get to
weighted extinction coefficient profiles or the weighted sum of aerosol and molecular extinction coefficient profiles.
Simultaneous measurements of aerosol column optical depth (at 500 nm) using a Microtops sun photometer were used in
the retrievals. The molecular extinction coefficient is determined assuming standard atmospheric conditions. The aerosol
extinction coefficient profiles are determined by subtracting the molecular part from the weighted extinction coefficient
profiles. The details of the method and the results obtained are presented.
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