Abstract: In one aspect, a graphics processing unit (GPU) data sniffing method includes the step of providing a video game software comprising a set of graphics data of a video game. The method includes the step of communicating the set of graphics data to a graphics library using an application programming interface (API) call to the graphics library. The graphics library includes at least one application API interface. The method includes the step of providing a sniffing module. The sniffing module intercepts the set of graphics data before the set of graphics data reaches the GPU. The sniffing module copies the set of graphics data to create a copy of the graphics data. The sniffing module forwards the copy of the graphics data to the graphics library for rendering to a receiving entity.

Abstract: 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.