Median filter

About: Median filter is a research topic. Over the lifetime, 12479 publications have been published within this topic receiving 178253 citations.

Adaptive hybrid mean and median filtering of high-ISO long-exposure sensor noise for digital photography

Abstract: This paper presents a new methodology for the reduction of sensor noise from images acquired using digital cameras at high- International Organization for Standardization (ISO) and long- exposure settings. The problem lies in the fact that the algorithm must deal with hardware-related noise that affects certain color channels more than others and is thus nonuniform over all color channels. A new adaptive center-weighted hybrid mean and median filter is formulated and used within a novel optimal-size windowing framework to reduce the effects of two types of sensor noise, namely blue-channel noise and JPEG blocking artifacts, common in high-ISO digital camera images. A third type of digital camera noise that affects long-exposure images and causes a type of sensor noise commonly known as ''stuck-pixel'' noise is dealt with by pre- processing the image with a new stuck-pixel prefilter formulation. Experimental results are presented with an analysis of the perfor- mance of the various filters in comparison with other standard noise reduction filters. © 2004 SPIE and IS&T. (DOI: 10.1117/1.1668279)

Spatio-Temporal Motion Compensated Noise Filtering Of Image Sequences

Abstract: In this paper the filtering of noise in image sequences using spatio-temporal motion compensated techniques is considered. Noise in video signals degrades both the image quality and the performance of subsequent image processing algorithms. Although the filtering of noise in single images has been studied extensively, there have been few results in the literature on the filtering of noise in image sequences. A number of filtering techniques are proposed and compared in this work. They are grouped into recursive spatio-temporal and motion compensated filtering techniques. A 3-D point estimator which is an extension of a 2-D estimator due to Kak [5] belongs in the first group, while a motion compensated recursive 3-D estimator and 2-D estimators followed by motion compensated temporal filters belong in the second group. The motion in the sequences is estimated using the pel-recursive Wiener-based algorithm [8] and the block-matching algorithm. The methods proposed are compared experimentally on the basis of the signal-to-noise ratio improvement and the visual quality of the restored image sequences.

High-throughput one-dimensional median and weighted median filters on FPGA

Abstract: Most effort in designing median filters has focused on two-dimensional filters with small window sizes, used for image processing. However, recent work on novel image processing algorithms, such as the Trace transform, has highlighted the need for architectures that can compute the median and weighted median of large one-dimensional windows, to which the optimisations in the aforementioned architectures do not apply. A set of architectures for computing both the median and weighted median of large, flexibly sized windows through parallel cumulative histogram construction is presented. The architecture uses embedded memories to control the highly parallel bank of histogram nodes, and can implicitly determine window sizes for median and weighted median calculations. The architecture is shown to perform at 72 Msamples, and has been integrated within a Trace transform architecture.