Animated ink and wash character modeling and simulation based on automatic intelligent matching of local pixel blocks.

Animation ink is a unique form of artistic expression, which is taken from traditional ink painting, and through the continuous exploration and advancement of animators, it has gradually formed its language system and formed a unique artistic style in expression and mood shaping. In this paper, the spatial domain noise reduction method and the transform domain noise reduction method are integrated, and the two types of algorithms complement each other to obtain a better denoising effect. The local pixel block matching algorithm is used to select similar block samples, which makes the covariance calculated by a principal component analysis more accurate in the next step, and then distinguishes the signal from the noise well. The adaptive bilateral filtering algorithm based on residual noise variance estimation uses the spatial proximity and pixel value similarity in the animated ink and wash image under the premise of the optimal set of filtering parameters, and adopts the local weighted average method to obtain the recovered animated ink and wash image. To effectively protect and enhance the detail information such as edges of the animated ink and wash image for animated ink and wash character modeling design. The method in this paper makes full use of the properties between spatial pixels of animated ink and wash images with both rotation invariance and translation invariance. The experimental results on the test database show that the method in this paper can extract features better. The purpose of this paper is to explore how to inherit and bring into play the fine cultural and artistic essence of ink art, to uncover the expressive elements applicable to animation ink character modeling design, and to make them reasonably and effectively used in the creation of animation ink character modeling to maintain the vitality of animation ink character modeling design. [ABSTRACT FROM AUTHOR]