3.1 Texture Synthesis Technology of Freehand Ink Painting
Texture synthesis is a popular technique for processing self-similar
images. It is a method to generate an output image with unlimited size
from a given input sample image. The output image is very similar to the
original sample by visual observation, but not strictly consistent. It
is through some small samples of mountain stone texturing that the
author synthesizes a large block of complete mountain stone texturing
texture, which solves the problem of the richness of texturing texture.
Because the texturing method of Chinese landscape painting is formed by
the combination of texturing, wiping, dyeing and spotting on suitable
paper with a brush dipped in ink, which is rich in changes. The
texturing method is usually composed of fine lines, which are closely
combined. Sometimes the lines are rendered layer by layer, and sometimes
only the texturing is wiped without stippling, thus forming the local
self similarity of the texturing method texture. However, the texture
structure of texturing method is not very obvious, and the shape is
irregular. Given these characteristics of the texturing method of
landscape painting, and considering the complexity of the algorithm, we
try to use the natural texture synthesis method [10] [11]
proposed by Ashikhmin, and combine the characteristics of the texturing
method rendering of Chinese landscape painting to improve and optimize
the algorithm accordingly. Finally, considering that the wrinkled
texture of landscape painting has a certain directionality, in the final
rendering, we use an alpha mask channel to guide its synthesis in
three-dimensional space, aiming to achieve an artistic effect of
freehand mountain and water painting similar to vivid charm, incisive
ink and rich colors.
Ashikhmin proposed the synthesis method of natural texture. The
so-called natural texture refers to the texture composed of some very
similar but irregular small units in shape and size. Ashikhmin uses the
correlation principle to limit the search scope to the neighborhood of
the current point. The method of synthesizing natural texture also uses
the L-shaped neighborhood of the current point, and the neighborhood
size is Neighb-siz. It is not in direct proportion to the texture
quality, and the optimal value depends on the texture structure.
Excessive neighborhood not only affects the synthesis speed but also
leads to a large number of repeated regions. when the texture is smooth,
the neighborhood needs to be increased. Firstly, a large number of
texturing methods in landscape paintings are collected and stored in the
system as input sample images. For simplicity, we first assume that both
the input sample image and the output image to be synthesized have
regular sizes. Using the principle of correlation, the algorithm limits
the search range to the neighborhood of the current point. According to
the L-neighborhood point, candidate pixels are obtained after the
corresponding position in the input image is shifted by a corresponding
amount. We define an array structure for each pixel in the output image
to store the position of the pixel in the input sample image, to
facilitate the search for matching points of neighboring pixels. Suppose
we copy the q point in the sample image to the pixel P in the output
image, we can establish a data structure s (.) with p as the index,
which has the following equation:
S (p )=q
In the calculation process, for each pixel synthesized, its position in
the input sample image is recorded in the structure. The algorithm first
initializes the array that records the positions of matching
points\sout,and sets it as a random point in the input image. For each
pixel in the output image, it is calculated according to the scanning
line order. In the output image, consider the L-neighborhood of the
current point, and for each point in the neighborhood, according to the
position of the matching point in the array, after offsetting the
corresponding position, select the point as the candidate point, to form
a list of candidate points and clear the duplicate candidate
points.
Select the point with the least L-neighborhood error with the current
point of the output image from the selected point, copy it to the
current point of the output image, and record the position. If
necessary, perform secondary or multiple syntheses until a satisfactory
texture image is obtained. Figure 4 is the texturing texture effect
picture synthesized by the author through texturing sampling for a
traditional Chinese landscape painting.