Robustifying Vector Median Filter

This paper describes two methods for impulse noise reduction in colour images that outperform the vector median filter from the noise reduction capability point of view. Both methods work by determining first the vector median in a given filtering window. Then, the use of complimentary information from componentwise analysis allows to build robust outputs from more reliable components. The correlation among the colour channels is taken into account in the processing and, as a result, a more robust filter able to process colour images without introducing colour artifacts is obtained. Experimental results show that the images filtered with the proposed method contain less noisy pixels than those obtained through the vector median filter. Objective measures demonstrate the goodness of the achieved improvement

Analisa Perbandingan Adaptif Median Filter dan Median Filter dalam Reduksi Noise Salt & Pepper

Suatu data atau informasi disajikan tidak hanya berupa data teks tetapi juga dapat berupa audio, video, dan gambar. Pada zaman sekarang informasi sangatlah penting dan diperlukan, begitu juga informasi yang terdapat pada citra. Citra (image) atau istilah lain untuk gambar merupakan salah satu komponen multimedia yang berperan penting sebagai bentuk informasi visual. Dibandingkan dengan data teks, citra memiliki banyak informasi. Namun terkadang citra juga dapat mengalami penurunan yaitu degradasi atau penurunan kualitas yang disebabkan oleh derau / noise, warna terlalu kontras, kabur, dan lain-lain. Ada beberapa jenis noise dalam pengolahan citra salah satunya yaitu Salt & Pepper noise. Noise Salt & Pepper berbentuk seperti bintik hitam dan putih pada citra. Untuk mengurangi noise ini dibutuhkan suatu metode, salah satunya yaitu median filter. Metode yang digunakan pada penelitian ini adalah median filter dan adaptif median filter. Perbedaan mendasar antara kedua metode ini yaitu pada besarnya windows pada adaptif median filter adalah variabel. Dari hasil penelitian, citra yang menggunakan metode adaptif median filter lebih baik daripada median filter. Dari perhitungan Peak Signal to Noise Ratio (PSNR) citra yang menggunakan adaptif median filter mendapatkan 29,2495 dB sedangkan median filter mendapatkan 23,8181 dB

Exhaustive Study of Median filter

Image filtering plays an important role to remove impulse (Salt and Pepper) noise from the images. The median filter which is a non - linear filter is very effective at removing noise while preserving image features and edges. In comparison to linear filter, they provide excellent noise reduction capabilities, with less blurring. The work ing of median filter is by removing the corrupted pixel value with the median value of neighboring pixel which is calculated by sorting all the pixel values from the window into ascending order. This paper presents a median filtering algorithm by using 3* 3 windows

Decision Based Adaptive Neighborhood Median Filter

AbstractImpulse noise in an image degrades the performances of the image processing and analysis stages. Therefore the noise removal and correction is an important processing required before performing any subsequent image processing approaches in the image data. In this paper a novel approach is proposed to remove the impulse noise from gray images. In this technique, all the pixels having gray value 0 and 255 are considered as the noisy pixels. The proposed method consists of three stages of filtering by considering the neighborhood pixels. The proposed method outperforms the Standard median Filter, Improved Fast Peer Group Filter and Modified Decision Based Unsymmetric Trimmed Median Filter

GPU Accelerated Vector Median Filter

Noise reduction is an important step for most image processing tasks. For three channel color images, a widely used technique is vector median filter in which color values of pixels are treated as 3-component vectors. Vector median filters are computationally expensive; for a window size of n x n, each of the n(sup 2) vectors has to be compared with other n(sup 2) - 1 vectors in distances. General purpose computation on graphics processing units (GPUs) is the paradigm of utilizing high-performance many-core GPU architectures for computation tasks that are normally handled by CPUs. In this work. NVIDIA's Compute Unified Device Architecture (CUDA) paradigm is used to accelerate vector median filtering. which has to the best of our knowledge never been done before. The performance of GPU accelerated vector median filter is compared to that of the CPU and MPI-based versions for different image and window sizes, Initial findings of the study showed 100x improvement of performance of vector median filter implementation on GPUs over CPU implementations and further speed-up is expected after more extensive optimizations of the GPU algorithm

Adaptive Marginal Median Filter for Colour Images

This paper describes a new filter for impulse noise reduction in colour images which is aimed at improving the noise reduction capability of the classical vector median filter. The filter is inspired by the application of a vector marginal median filtering process over a selected group of pixels in each filtering window. This selection, which is based on the vector median, along with the application of the marginal median operation constitutes an adaptive process that leads to a more robust filter design. Also, the proposed method is able to process colour images without introducing colour artifacts. Experimental results show that the images filtered with the proposed method contain less noisy pixels than those obtained through the vector median filter

Interference detection and correction applied to incoherent-scatter radar power spectrum measurement

A median filter based interference detection and correction technique is evaluated and the method applied to the Arecibo incoherent scatter radar D-region ionospheric power spectrum is discussed. The method can be extended to other kinds of data when the statistics involved in the process are still valid

Video denoising using fuzzy-connectedness principles

Fuzzy-connectedness principles are effective for image segmentation. In this paper, such a principle is applied to video denoising. Assume a video signal suffers from both additive white Gaussian noise and impulsive noise. The corrupted signal is filtered by a fuzzy system, which fuzzily connects a Wiener filter and a median filter together. The simulation results show that the fuzzy-connectedness approach produces desirable outputs