An Image Terrain Map Model for Texture Filtering

The purpose of texture measurement is to describe and quantify the texture features of pixels in an image. The accuracy of texture measurement plays a crucial role in determining the effectiveness of texture filtering. However, current texture measurement methods face challenges in achieving accurate texture measurement results, particularly for multi-scale texture measurements. This limitation often leads to unsatisfactory texture filtering results, particularly with image details and high-contrast textures. We find that when moving the texture measurement regions for pixels near texture edges further away from the texture edge and keeping the texture measurement regions for pixels far from texture edges unchanged results in an improved accuracy of texture measurement. Based on this observation, we propose a novel texture measurement approach that employs a circular neighborhood with a variable radius as the texture measurement region for each pixel. Furthermore, we proposed an image terrain map model based on a one-pixel texture edge to obtain optimal parameters for texture measurement regions. This model significantly enhances the accuracy of texture measurement at any scale in an image. The experimental results show that the texture filtering method based on our image terrain map model is significantly better than existing methods in terms of edge-preservation, small-structure preservation, and high-contrast texture filtering. Additionally, we presented some applications of the image terrain map model in other areas of image processing to demonstrate its versatility.