Noise is inevitably common in digital images, leading to visual image deterioration.
Therefore, a suitable filtering method is required to lessen the noise while preserving the …

Image denoising has gained in relevance as a component of image preprocessing due to
the increased use of digital images in a range of applications, as well as the degradation of …

This paper proposes a Generalized Multilevel B-spline Approximation (GMBA) method,
which addresses scattered data interpolation problems in image processing …

This book offers a detailed insight of artificial intelligence (AI) algorithms for image dehazing
and non-uniform illumination enhancement. In this book, various image enhancement …

Noise in images refers to random variations in pixel intensities that alter the original pixel
intensities of the image. Among the various noises present in the image, salt and pepper …

This chapter presents a single image dehazing method employing a Type-2 membership
function based similarity function matrix. The approach involves estimating the depth map …

This chapter presents the introduction of an Adaptive Interval Type-2 Fuzzy Filter. This filter
is presented as one of the artificial intelligence agents for the preservation of naturalness in …

In the previous chapter, the unsupervised image dehazing method was explained, which
deals with over-saturation challenges. This chapter delves into a detailed exploration of the …

Noise is inevitably common in digital images, leading to visual image deterioration.
Therefore, a suitable filtering method is required to lessen the noise while preserving the …

This chapter introduces an image enhancement approach utilizing the Z-score for images
captured under hazy and non-uniform illumination conditions, with a focus on applications in …