Preliminary study of improved median filter using adaptively mask size in light microscopic image

Abstract

This study aimed to develop and evaluate an improved median filter (IMF) with an adaptive mask size for light microscope (LM) images. We acquired images of the mouse first molar using a LM at 100× magnification. The images obtained using our proposed IMF were compared with those from a conventional median filter. Several parameters such as the contrast-to-noise ratio, coefficient of variation, no-reference assessments and peak signal-to-noise ratio were employed to evaluate the image quality quantitatively. The results demonstrated that the proposed IMF could effectively de-noise the LM images and preserve the image details, achieving a better performance than the conventional median filter.

Blind Deconvolution Based on Compressed Sensing with bi-l0-l2-norm Regularization in Light Microscopy Image

“…Recently, methods for evaluating the sharpness index of an image based on no-reference including the blind/referenceless image spatial quality evaluator or image quality evaluator parameter have been developed and used [33][34][35]. In researches by Kim et al, a no-reference-based method was used to evaluate the noise removal efficiency that is not revealed in the visual evaluation when the denoising algorithm is applied to the light microscopy image [1]. However, since this index has the disadvantage that it cannot accurately measure edge information, it is rarely used as a general method for microscopic image evaluation.…”

“…Although a light microscope can be used to most easily observe the changes in the tissue, it is limited in observing fine parts owing to the limitations of spatial resolution and noise amplification. Thus, it is essential to improve the qualities of light microscopic images for accurate analysis [1]. The approach of development of hardware and software technologies is mainly used to improve the microscopic image quality.…”