A Novel Color Microscope Image Enhancement Method Based on HSV Color Space and Curvelet Transform

A new method which is suitable for enhancing the color microscopic image quality based on HSV color space and curvelet transform is presented in this paper. The color microscopic image is firstly divided into hue, saturation and value components from RGB color space to HSV color space through the color space conversion. The value component is decomposed by the curvelet transform. A modulus square function and a linear gain operator are applied to the high frequency curvelet coefficients to reduce noise and weight the detail. Then, the processed curvelet coefficients are reconstructed in order to obtain the enhanced value component by inverse wavelet transform. The saturation component is enhanced by adaptive histogram equalization. The enhanced value and saturation components together with unchanged hue component are finally converted back RGB color space. The experimental results show that the proposed method effectively enhances the color microscopic image which is better to reduce noise and render the clarity and colorfulness of the original image.