Miranda Technologies Inc.

Algolith Inc.

Ha Do Viet

Chon Tam Le Dinh

Cong Toai Kieu

Ngoc Lan Nguyen

Thi Thanh Hien Nguyen

Duong Tuan Nguyen

An efficient and non-iterative 3D post processing method and system is proposed for mosquito noise reduction, block localization and correction in DCT block-based decoded images. The 3D post processing is based on a simple classification that segments a picture in multiple regions such as Edge, Near Edge, Flat, Near Flat and Texture regions. The proposed technique comprises also an efficient and shape adaptive local power estimation for equivalent additive noise and provides simple noise power weighting for each above cited region. Temporal filtering configurations using Minimum Noise Variance Criterion are proposed for reducing temporally varying coding artifacts. A Minimum Mean Square Error or Minimum Mean Square Error-like noise reduction with robust and effective shape adaptive windowing is utilized for smoothing mosquito and/or random noise for the whole image, particularly for Edge regions. The proposed technique comprises also signal domain histogram analysis based Block Localization and adaptive edge based Block artifact correction. Finally, is also proposed an optional adaptive detail enhancer which can enhances the luminance signal in eight directions differently.

Apparatus and method for adaptive 3D artifact reducing for encoded image signal

The basic configuration of Single local Adaptive Window Spatial Noise Reducer (SAW-SNR) is based on a preliminary de-noising low-pass filter followed by homogenous region segmentation to the considered pixel in a given local window. The configuration is composed also of an adaptive local mean estimator, an adaptive local statistic estimator which is preferably an economic standard deviation (SD) estimator and finally, a minimum-mean-square-error (MMSE) based de-noising technique. The proposed segmentation configuration outperforms existing spatial noise reducers in term of subjective and objective performances, in term of edge preservation, noise reduction in both homogenous regions or picture edges and Peak Signal to noise Ratio (PSNR). A second configuration in the form of a Parallel Multiple local Adaptive Window Spatial Noise Reducer (Parallel M-AW-SNR), is a combination of several basic configurations which implements different segmented windows. The M-AW-SNR, which is the less complex configuration for multiple spatial noise reducers, reduces further residual noise as compared to the basic configuration. A third configuration combines the basic configuration of SAW-SNR with a controllable noise variance estimator. This generic configuration allows an adaptive local control of noise reduction level, which can be useful for some correlated noise such as ringing noise in DCT-based decompressed images or cross-luminance noise in composite decoded images.

Apparatus and method for adaptively reducing noise in a noisy input image signal

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