Adaptive rendering method using linear prediction
An adaptive rendering and linear prediction technology, applied in the field of adaptive rendering, can solve the problems of high computing overhead and achieve the effect of reducing computing overhead
Patent Information
- Authority / Receiving Office
- CN · China
- Current Assignee / Owner
- Publication Date
- 2016-07-13
- Estimated Expiration
- Not applicable · inactive patent
Smart Images
Figure 1 Figure 2 Figure 3
Abstract
Description
technical field
[0001] The invention relates to the technical field of computer image processing, in particular to an adaptive rendering method using linear prediction. Background technique
[0002] Monte Carlo ray tracing has gained a lot of attention for artificially rendering realistic rendering effects, but generally requires a large number of ray samples (e.g., more than 10,000 samples per pixel) until a fused or visually pleasing image.
[0003] The slow fusion process of Monte Carlo ray tracing directly leads to excessive rendering times (in hours), which are generally proportional to the number of generated ray samples. When a relatively small number of ray samples (less than a thousand) are allocated at a pixel, the image is generally polluted by MC noise, ie biased.
[0004] Adaptive rendering, which non-uniformly adjusts the sampling density and uses local smoothing, has been actively researched in recent years. This method greatly improves the efficiency of MC ...
Examples
Embodiment Construction
[0050] The present invention will be described in detail below in conjunction with specific embodiments.
[0051] Such as figure 1 As shown, an adaptive rendering method using linear prediction, including:
[0052] Step 1, reconstruct the image using a local linear model.
[0053] First define a filter window The filter window is centered on pixel c. A filter window can be viewed as a collection of all pixels within the window.
[0054] Define another prediction window Including Note the filter window There is a global fixed size, which is 19*19 in this embodiment. in the forecast window In , the real image f(x) is predicted using a linear model with variable k.
[0055] Within the prediction window, a linear model is defined by a first-order Taylor polynomial centered at pixel c as follows:
[0056] (T indicates that the item is predicted by the least square method)
[0057] where x i Represents a feature vector at pixel i; x c Represents a feature vector ...