Hot news:

If you find a spelling error, please select an incorrect text and press Ctrl+Enter. Thank you!

Compression project >> Video Area Home
RUSSIAN VERSION

MSU Cartoon Restore Filter 2.0 beta

Filter for quality improvement of compressed animated video

MSU Graphics & Media Lab (Video Group)

Method ideas: Dr. Dmitriy Vatolin,
Alexander Parshin
Implementation: Alexey Moiseytsev, Arsaev Marat

One of the most prominent coding artifacts in highly compressed animated video are the ringing artifacts. Ringing noise preferably manifest itself around edges due to coarse quantization. The filter is designed for quality improvement of compressed cartoons like video by deleting ringing artifacts.


Change Log


Version 2.0b
[+] Added GPU implementation.
[+] Filter performance increased

Version 1.3
[+] GUI improvement
[+] Added motion adaptive mode (filter speedup!)
[+] Added new algorithm Image Similarity (beta version)

Version 1.1
[+] First filter release

Comparison with version 1.3

for configuration: Inter Core2Duo T7300 2.0GHz, Nvidia 8600M GT, 2.0GB RAM, ForceWare 174.31
comparison

Settings



Simple mode


Filter's main window

This mode allows you select one of several presets, without additional manual filter tuning. "GPU Usage" checkbox will enable GPU mode if available. Simple mode settings:


Advanced mode


This mode allows configure filter manually and get best quality for particular video. For all methods "Use GPU" checkbox enables GPU mode.

Combo box "Method" allows select one of four implemented algorithms.

Simple Adaptive Filter

Filter's main window
Filter parameters:

Fuzzy Adaptive Filter

Filter's main window
The filtration strength depends on amount of details in each block. Left sliders correspond to blocks without details, and right sliders correspond to edge blocks.

There are some presets, which allow quickly selecting filter configuration (use "Preset" list).

Multipass Bilateral Filter

Filter's main window
Filter parameters: Also some general presets can be selected.

Similarity DB Filter (beta version)

We are still working on this algorithm quality improvement. This version can demonstrate suboptimal results!

Filter's main window
The Strength parameter of the filter sets strength of a filtration of video.
This filter requires the additional artifact.db file.

Job control and integration with AviSynth


Filter supports VirtualDub Job Control, and it can be used from AviSynth. Some examples are listed below.

Simple Adaptive Filter:

LoadVirtualDubPlugin("MSU_cartoon_restore.vdf","MSUCartoonRestore", 0) 
clip=AVISource("D:\work\video\film.avi", false, "RGB24")
clip.ConvertToRGB32.MSUCartoonRestore("simple", Smoothness, Threshold, GPUUsage)
Fuzzy Adaptive Filter:
LoadVirtualDubPlugin("MSU_cartoon_restore.vdf","MSUCartoonRestore", 0) 
clip=AVISource("D:\work\video\film.avi", false, "RGB24")
clip.ConvertToRGB32.MSUCartoonRestore("fuzzy", Strength10, Strength20, Strength30, Strength40, Strength50, Strength60, Strength70, Strength80, Strength90, Strength100, ShowBlockType)
Multipass Bilateral Filter:
LoadVirtualDubPlugin("MSU_cartoon_restore.vdf","MSUCartoonRestore", 0) 
clip=AVISource("D:\work\video\film.avi", false, "RGB24")
clip.ConvertToRGB32.MSUCartoonRestore("bilateral", Iterations, GeometricDispersion, PhotometricDispersion)

Examples


Source frame
Source frame
MSU Cartoon Restore
Frame processed by MSU Cartoon Restore
Source frame
Source frame
MSU Cartoon Restore
Frame processed by MSU Cartoon Restore

Source frame
Source frame
MSU Cartoon Restore: Simple Adaptive Filter
Simple Adaptive Filter
MSU Cartoon Restore: Fuzzy Adaptive Filter
Fuzzy Adaptive Filter
MSU Cartoon Restore: Multipass Bilateral FIlter
Multipass Bilateral FIlter


Download


E-mail: 
Please read MSU filters FAQ before mailing.


Other resources


Video resources:

Bookmark this page:   Add to Del.icio.us Add to Del.icio.us     Digg It Digg It     reddit reddit

 
Last updated: 10-March-2011

Search (Russian):
Server size: 8069 files, 1215Mb (Server statistics)

Project updated by
Server Team and MSU Video Group


Project sponsored by YUVsoft Corp.

Project supported by MSU Graphics & Media Lab