| Operators |
inpainting_texture — Perform an inpainting by texture propagation.
inpainting_texture(Image, Region : InpaintedImage : MaskSize, SearchSize, Anisotropy, PostIteration, Smoothness : )
The operator inpainting_texture is used for removing large objects and image errors from the region Region of the input image Image. Image blocks of side length MaskSize are copied from the intact part of the image to the border of the computation area, until that area has been filled up with new gray values. This process is called image inpainting. Hence, the computation area is also referred to as the inpainting area and is reduced with every inserted rectangle, starting with Region. Let the center of the current block be at the point x. Since x is always chosen from the border of the inpainting area the current block overlaps with the known or already filled-in gray values. The gray value correlation with the overlapping part of this block is used to determine which other image block fits at the position x. As the correlation function, the sum of the squared gray value differences is used. The image blocks that are taken into account for the correlation, and hence as candidates for the data source of the next inpainting step, are called comparison blocks. The search area for suitable gray value patterns in which the centers of the comparison blocks is searched is limited to a square of side length 2*SearchSize around the point x.
On the one hand, the order in which the pixels of Region are filled in depends on the size of the overlapping area and thus the number of pixels available for the correlation. On the other hand, the absolute value of the derivative of the gray value function tangential to the border of the computation area is also considered. The larger the value of the parameter Anisotropy is, the more the points in which the derivative is large are preferred. This way it can be achieved that, e.g., straight lines which are represented by large gradients, are continued through the entire computation area without being interrupted by the inpainting of image structures from other parts of the border when the size of the inpainting area becomes small. On the other hand, a large value of Anisotropy also means that possible phantom edges, i.e., unwanted random structures that have developed during the inpainting process, are also propagated and the magnitude of those image disturbances is increased.
To confine the formation of such artifacts, the original algorithm can be extended by a post-iteration step that selects smooth and inconspicuous image patches as data sources for the inpainting. If the parameter PostIteration is set to 'min_grad' the sum of the squares of the gray value gradients is minimized on the comparison blocks. With the value 'min_range_extension', the growth of the gray value interval of the comparison blocks with respect to the reference block around the point x is minimized. If PostIteration has the value 'none' no post-iteration is performed. The choice of feasible blocks for this minimization process is determined by the parameter Smoothness, which is an upper limit to the permitted increase of the mean absolute gray value difference between the comparison blocks and the reference block with respect to the block that was selected by the original algorithm. With increasing value of Smoothness, the inpainting result becomes smoother and loses structure. The matching accuracy of the selected comparison blocks decreases. If Smoothness is set to 0, the post-iteration only considers comparison blocks with an equally high correlation to the reference block.
If the inpainting process cannot be completed because there are points x, for which no complete block of intact gray value information is contained in the search area of size SearchSize, the remaining pixels keep their initial gray value and the ROI of the output image InpaintedImage is reduced by the region that could not be processed. If the structure size of the ROI of Image or of the computation area Region is smaller than MaskSize, the execution time of the algorithm can increase extremely. Hence, it is recommended to only use clearly structured input regions.
Note that filter operators may return unexpected results if an image with a reduced domain is used as input. Please refer to the chapter Filters.
Input image.
Inpainting region.
Output image.
Size of the inpainting blocks.
Default value: 9
Suggested values: 7, 9, 11, 15, 21
Restriction: MaskSize >= 3 && odd(MaskSize)
Size of the search window.
Default value: 30
Suggested values: 15, 30, 50, 100, 1000
Restriction: 2 * SearchSize > MaskSize
Influence of the edge amplitude on the inpainting order.
Default value: 1.0
Suggested values: 0.0, 0.01, 0.1, 0.5, 1.0, 10.0
Restriction: Anisotropy >= 0
Post-iteration for artifact reduction.
Default value: 'none'
List of values: 'min_grad', 'min_range_extension', 'none'
Gray value tolerance for post-iteration.
Default value: 1.0
Suggested values: 0.0, 0.1, 0.2, 0.5, 1.0
Restriction: Smoothness >= 0
Foundation
| Operators |