Algolith Inc.

Miranda Technologies Inc.

Chon Tam Le Dinh

Cong Toai Kieu

Thi Thanh Hien Nguyen

Ngoc Lan Nguyen

Ha Do Viet

Duong Tuan Nguyen

Daniel Poirier

François Rossignol

Hong Thai 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

A new approach to objective quality assessment of DCT-coded video sequences, with or without a reference is proposed. The system is comprised of a proprietary segmentation algorithm, a feature extraction process and a nonlinear feed-forward-type neural network for feature analysis. The methods mimic function of the human visual system (HVS): A neural network training algorithm is used for determining the optimal network weights and biases for both system modes of operation. The proposed method allows for assessment of DCT-coded video sequences without the original source being available (pseudo-reference mode). The pseudo-reference mode is also comprised of a proprietary DCT-coded video (MPEG) noise reducer (MNR), co-pending patent application No. 60/592,143.

Apparatus and method for objective assessment of DCT-coded video quality with or without an original video sequence

The present description discloses a method for resizing an input image having input pixels. The method comprises segmenting the input made into region types by assigning one of the region types to each one of the input pixels; and interpolating the input image according to the region type assigned to each one of the input pixels to produce a resized image having interpolated pixels.

Content adaptive resizer

A non-iterative 3D processing method and system is disclosed for generic noise reduction. The 3D noise reducer is based on a simple conversion of the five types of noise to equivalent additive noise of varying statistics. The proposed technique comprises also an efficient temporal filtering technique which combines Minimization of Output Noise Variance (MNV) and Embedded Motion Estimation (EME). The proposed temporal filtering technique may be furthermore combined with classical motion estimation and motion compensation for more efficient noise reducer. The proposed technique comprises also a spatial noise reducer which combines Minimum Mean Squared Error (MMSE) with robust and effective shape adaptive windowing (SAW) is utilized for smoothing random noise in the whole image, particularly for edge regions. Another modification to MMSE is also introduced for handling banding effect for eventual excessive filtering in slowly varying regions.

Apparatus and method for adaptive 3D noise reduction

An efficient and non-iterative post processing method and system is proposed for mosquito noise reduction in DCT block-based decoded images. The 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. An MMSE or MMSE-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. Finally, the proposed technique comprises also, for chrominance components, efficient shape adaptive local noise power estimation and correction.

Apparatus and method for adaptive spatial segmentation-based noise 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

An electronic apparatus for converting a standard video signal having 59.94 fields per second into an HDTV video signal having 60.00 fields per second, by adding a number of video fields into each sequence of 1000 video fields. The apparatus detects the best moment for adding the new video field, so that the human eye does not perceive an abrupt change in the video image, by detecting the best motion conditions which occurs either when the image motion is high or very low. For adding the new video field, the apparatus uses an interpolation technique for creating two interpolated video fields which are inserted in place of one existing video field which is deleted. The apparatus also comprises a de-interlacer module for deinterlacing the 60 Hz video image, by using an advanced interpolation technique for calculating the missing video lines. The proposed technique involves directional interpolations of the missing lines pixels in various directions and selection of the best interpolation direction for the creation of each pixel of the missing video lines. The corresponding de-interlacer apparatus comprises a novel edge direction detector which performs the mentionned interpolations in all interpolating directions and then selects the best direction for performing the interpolation for each interpolated pixel, based on the quality of the performed interpolations.

Growing community of inventors

Montreal, Canada

Chon Tam Le Dinh