Image Downsampling

Image downsampling aims to reduce image resolution while minimizing information loss and preserving key features. Current research focuses on developing algorithms that go beyond simple interpolation techniques, incorporating factors like wavelet transforms to maintain crucial details in low-frequency components, topology preservation for binary images, and edge-aware probabilistic methods for medical image segmentation. These advancements are crucial for improving efficiency in various applications, including real-time rendering of 3D models, medical image analysis, and low-light image enhancement, by enabling processing of high-resolution data on resource-constrained systems.