Parametric Image

Parametric images represent data using parameters that describe image features rather than raw pixel values, enabling efficient representation and manipulation of complex visual information. Current research focuses on improving the generation and editing of these images, employing techniques like diffusion models and convolutional neural networks to optimize processes such as segmentation-based painting and speckle statistics estimation in applications like quantitative ultrasound. These advancements enhance image quality, reduce computational costs, and improve the accuracy of parameter estimation, with implications for diverse fields including medical imaging, computer graphics, and artistic creation.