Image Enhancement Using Homomorphic Filtering and Adaptive Median Filtering for Balinese Papyrus (Lontar)

Image Enhancement Using Adaptive Filtering

In this paper, we develop an image enhancement algorithm that modifies the local luminance mean of an image and controls the local contrast as a function of the local luminance mean of the image. The algorithm first separates an image into its lows (low pass filtered form) and highs (high pass filtered form) components. The lows component then controls the amplitude of the highs component to in...

Medical Image Enhancement Techniques by Bottom Hat and Median Filtering

This paper presents an efficient method for medical 2-D image enhancement technique using median and bottom hat filtering, that can also be used in image processing such as medical image reconstruction, image smoothing, feature extraction and image analysis. We present a comparison of these filters using the medical images. After filtering also the input image or actual image have some noise th...

Digital image enhancement: vector median filter and peer group filtering

Speech Enhancement by Modified Convex Combination of Fractional Adaptive Filtering

This paper presents new adaptive filtering techniques used in speech enhancement system. Adaptive filtering schemes are subjected to different trade-offs regarding their steady-state misadjustment, speed of convergence, and tracking performance. Fractional Least-Mean-Square (FLMS) is a new adaptive algorithm which has better performance than the conventional LMS algorithm. Normalization of LMS ...

A Robust De-Noising Model for Image Enhancement with Adaptive Median Filtering

This paper presents a robust de-noising model for image enhancement using adaptive median filtering. In this approach image noise is detected with a standard median filter using an adaptive window. Within the window, the original value of the center pixel is changed to a newer that is closer to or same as the standard median. A comparison has been arranged among the proposed method, the standar...