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Related Experiment Video

Updated: Jul 7, 2026

A Simple Technique to Assay Locomotor Activity in Drosophila

A Simple Technique to Assay Locomotor Activity in Drosophila

Published on: February 24, 2023

The digital TV filter and nonlinear denoising.

T F Chan¹, S Osher, J Shen

¹Department of Mathematics, University of California, Los Angeles, CA 90095-1555, USA. chan@math.ucla.edu

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society

|February 6, 2008

Summary

We introduce the digital total variation (TV) filter, a novel nonlinear filter for image denoising and enhancement. This data-dependent lowpass filter preserves edges and jumps while effectively removing noise from various data types.

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Last Updated: Jul 7, 2026

A Simple Technique to Assay Locomotor Activity in Drosophila

A Simple Technique to Assay Locomotor Activity in Drosophila

Published on: February 24, 2023

Area of Science:

Image Processing
Computer Vision
Signal Processing

Background:

Classical total variation (TV) restoration models are foundational in image processing.
Existing filters can blur essential image features like edges and jumps.
Denoising data on graphs requires specialized, robust methods.

Purpose of the Study:

To introduce a novel nonlinear filter, the digital TV filter, for image denoising and enhancement.
To develop a filter capable of preserving image details like edges and jumps.
To extend denoising capabilities to general data living on graphs.

Main Methods:

The digital TV filter is a data-dependent lowpass filter.
It iteratively solves a global total variational (L(1)) optimization problem.
The method is applied to various data types including 1-D signals, 2-D data, grayscale and color images.

Main Results:

The digital TV filter effectively denoises data without blurring edges or jumps.
Successful applications demonstrated on diverse datasets including irregular structures and nonflat image features.
The filter shows versatility in handling grayscale, color, and chromaticity data.

Conclusions:

The digital TV filter offers a powerful new approach for image denoising and enhancement.
Its ability to preserve structural details makes it superior to traditional filters.
The filter's adaptability to graph-based data opens new avenues for signal processing research.