We present a new technique for image contrast enhancement via multiscale gradient transformation. In contrast to histogram-based techniques which aim to change the global statistical distribution of pixel intensities, we improve image contrast by modifying the modulus of the gradient image at multiple scales. In computation, a multiscale gradient representation of the image is generated by a wa...

This paper presents an optimal contrast enhancement approach for remote sensing images based on dominant brightness level analysis and adaptive intensity transformation for remote sensing images. The proposed system first perform discrete wavelet transform (DWT) on the input images and then split the LL sub band into low-, middle-, and high-intensity layers using the logaverage luminance. The k...

Inconsistency in contrast enhancement can be used to expose imagel forgeries. In this work, we describe a new method to estimate contrast enhancement from a single image. Our method takes advantage of the nature of contrast enhancement as a mapping between pixel values, and the distinct characteristics it introduces to the image pixel histogram. Our method recovers the original pixel histogram ...

We present an interactive contrast enhancement technique for the global histogram modification of images. Through direct manipulation, the user adjusts contrast by clicking on the image. Contrast around different key tones can be adjusted simultaneously and independently without altering their luminance. Histogram warping by monotonic splines performs the gray level mapping. User interfaces for...

A new approach to contrast enhancement of mail piece images is presented. The contrast enhancement is used as a preprocessing step in the real-time address block location (RT-ABL) system. The RT-ABL system processes a stream of mail piece images and locates destination address blocks. Most of the mail pieces (classified into letters) show high contrast between background and foreground. As an e...

This paper studies various research contributions in the field of contrast enhancement of medical images. Medical images such as X-rays, ultrasound and others are used in the analysis and diagnosis process by physicians and radiologists. If the image quality is not good and contrast is poor then the diagnosis result is badly affected. Therefore, this paper attempts to review the research papers...

This paper describes a technique for image contrast enhancement. This technique is based on localized contrast manipuladon. This technique is easy to implement and have several properties such as adaptive, multiscale and weighted localization. This paper also describes an anisotropic propagation for this technique. Several examples for medical images such as Chest CT image, Brain MR images, Mam...

Several other methods of achieving dynamic range control were also discussed in the previous chapter. These methods are typically unsharp mask filters with large kernel sizes, and multi-scale approaches such as multi scale image contrast amplification (MUSICA) developed by the Agfa-Gevaert company (Vuylsteke & Schoeters, 1999). In achieving their goal of dynamic range control, these methods alt...

Segmentation of Grey/White/CSF from MR images depends on contrast to noise ratios (CNR) among these tissues and the CSF. The CNRs are determined by the acquisition method and imaging parameters. These factors can be optimized for improved image segmentation [1,21. In many MR studies, multiple images of the same slice locations are acquired, each with different weightings based Tl/T2/proton dens...

We present an automated algorithm for global contrast enhancement of images with multimodal histograms. To locate modes and valleys, histogram analysis is performed by kernel density estimation, a robust nonparametric statistical method. Histogram warping by monotonic splines pushes the modes apart, spreading them out more evenly across the dynamic range. This technique can assist in the contra...