Explain Mesh-based warping Answer:- Mesh-based warping is a powerful technique used to apply complex and flexible spatial transformations to images. Unlike parametric transformations (e.g., affine or projective) which use a small number of global parameters, mesh-based warping allows for local…
Explain Inverse warping algorithm for creating an image g(x) from an image f(x) using the parametric transform x= h(x) Answer:- In image processing and computer vision, geometric transformations are used to change the spatial layout of an image. The inverse…
Explain Forward warping algorithm for transforming an image f(x) into an image g(x) through the parametric transform x= h(x) Answer:- In image processing and computer vision, geometric transformations are used to remap pixel coordinates from a source image f(x) to…
Explain Geometric transformations and Parametric transformations Answer:- In computer vision and image processing, geometric transformations refer to operations that change the spatial arrangement of pixels in an image. These transformations allow tasks such as: aligning images, registering different views, simulating…
Describe Wavelets. How are Two-Dimensional Wavelets Constructed? Wavelets are a type of multi-resolution image representation, similar to image pyramids but with several important enhancements. Unlike Gaussian or Laplacian pyramids that simply create low-pass and band-pass versions of images, wavelets decompose…
Linear filtering is a fundamental operation in image processing and computer vision. It is used to modify or enhance an image by applying a filter (kernel) over a local neighborhood of pixels. The result is a new image in which…
Histogram Equalization – Step-by-Step Explanation Histogram equalization is a contrast enhancement technique in image processing. It works by redistributing the intensity values of an image so that the histogram of the output image becomes more uniform. This improves the visual…
Point Operators in Image Processing In computer vision and image processing, point operators (also known as point processes) are fundamental tools used to modify images at the pixel level. Each pixel is processed independently of its neighbors, making point operators…
The Bidirectional Reflectance Distribution Function (BRDF) is a key concept in photometric image formation. It defines how light is reflected at an opaque surface, describing how incoming light from one direction is reflected into another direction. This function is crucial…
Photometric image formation is a fundamental concept in computer vision that explains how light interacts with objects in a scene and how this interaction results in the brightness and color values captured in an image. While geometric image formation deals…
