Pixel classification algorithms for noise removal and signal preservation in low-pass filtering for contrast enhancement

With a view to obtaining a high quality contrast enhancement, low-pass filters are used to remove the noise generated in a high-gain histogram equalization process. To preserve signal variations, the LP operation applied to the pixels in non-homogeneous regions should have less smoothing strength than that in homogeneous regions. The pixel classification according to the gray level homogeneity is thus a critical part in the LP filtering. In this paper, two algorithms for pixel classification according to the gray level homogeneity of their regions are proposed. In each of them, image pixels are grouped in such a way that, in the same group, pixels in homogeneous regions can be easily distinguished from those in non-homogeneous regions by a simple gradient thresholding, despite the complexity of signal gradient degradation in images. The two proposed classification algorithms are very simple, requiring very small quantity of computation. Their effectiveness has been proven by the simulation results

High Dynamic Range Image Watermarking Robust Against Tone-Mapping Operators

High dynamic range (HDR) images represent the future format for digital images since they allow accurate rendering of a wider range of luminance values. However, today special types of preprocessing, collectively known as tone-mapping (TM) operators, are needed to adapt HDR images to currently existing displays. Tone-mapped images, although of reduced dynamic range, have nonetheless high quality and hence retain some commercial value. In this paper, we propose a solution to the problem of HDR image watermarking, e.g., for copyright embedding, that should survive TM. Therefore, the requirements imposed on the watermark encompass imperceptibility, a certain degree of security, and robustness to TM operators. The proposed watermarking system belongs to the blind, detectable category; it is based on the quantization index modulation (QIM) paradigm and employs higher order statistics as a feature. Experimental analysis shows positive results and demonstrates the system effectiveness with current state-of-art TM algorithms

High Dynamic Range Image Tone Mapping Based on Local Histogram Equalization

High Dynamic Range (HDR) images can represent the acquired scene with a greater dynamic range of luminance than classical Low Dynamic Range (LDR) ones. Despite the recent diffusion of some HDR camera models, HDR displays are not yet in the market. For this reason HDR images need to be adapted in order to be properly rendered through conventional devices. This operation mainly consists in a dynamic range compression realized by applying a Tone Mapping Operator (TMO). In this work, a new tone map algorithm, derived from the Contrast Limited Adaptive Histogram Equalization (CLAHE) technique, is presented. With respect to the original CLAHE, in the proposed implementation an adaptive contrast limit and a new strategy for the determination of local tone mapping functions have been introduced. The comparison between the obtained LDR images, and those produced by applying State of the Art TMOs, evidences how the main characteristic of the proposed algorithm is the ability to equally enhance visibility in both dark and bright areas. This could be, for example, a key feature in video surveillance applications and automotive safety camera systems

Pixel Classification Algorithms for Noise Removal and Signal Preservation in Low Pass Filtering

Contrast enhancement is essential to improve the image quality in most of image pre-processing. A histogram equalization process can be used to achieve a high contrast. It causes, however, also noise generation. Involving a low-pass filtering process is an effective way to achieve a high-quality contrast enhancement with low-noise, but it leads to the conflict between noise removal and signal preservation. To perform discriminative low-pass filtering operations with the presence of noises and signal variations in different regions, it is thus necessary to develop good algorithms to classify the pixels. In this thesis, two classification algorithms are proposed. They aim at low-contrast images where gradient signals are severely degraded by various causes during the acquisition process. They are to classify the pixels according to the initial gray-level homogeneity of their regions. The basic classification method is done by gradient thresholding, and the threshold values are generated by means of gradient distribution analysis. To tackle the problems of various gradient degradation patterns in low-contrast images, image pixels are grouped in a particular way that, in the same group, pixels in homogeneous regions can be easily distinguished from those in non-homogeneous regions by the basic method of simple gradient thresholding. Two algorithms based on different grouping methods are proposed. The first algorithm aims at high dynamic range images. The pixels are first grouped according to their gray-level ranges, as the gradient degradation is, in such a case, gray-level-dependent. The gradient distribution of each sub-range is obtained and a pixel classification is then made to adapt to their original gray-level signals in the sub-range. The other algorithm is to tackle a wider range of low-contrast images. In this algorithm, a gray-level histogram thresholding is performed to divide the pixels into two groups according to their likelihood to homogeneous, or non-homogeneous, pixels. Thus, in one group a majority of homogeneous pixels is established and in the other group the majority is of non-homogeneous pixels. The classification done in each group is to identify those in the minority. Both proposed algorithms are very simple in computation and each of them is incorporated into the contrast enhancement procedure to make the integrated low-pass filters effectively remove the noise generated in the histogram equalization while well preserving the signal details. The simulation results demonstrates, by subjective observation and objective measurements, that the proposed algorithms lead to a superior quality of the contrast enhancement for varieties of images, with respect to two advanced enhancement schemes

Local tone mapping operator for detail preserving reproduction of high dynamic range images.

Opseg osvetljaja koji se javlja u prirodnim scenama uveliko prevazilazi mogućnosti standardnih uređaja za snimanje i reprodukciju slike. Ljudski vizuelni sistem je evoluirao, tako da omogući efikasno funkcionisanje i percepciju detalja u uslovima velike promene osvetljaja. Kako bi se omogućila što realnija reprodukcija slika i video sadržaja, potrebno je obezbediti mogućnost snimanja i reprodukcije što šireg dinamičkog opsega osvetljaja. Razvoj tehnika za snimanje je napredovao i danas postoji mogućnost snimanja celokupnog dinamičkog opsega osvetljaja scene korišćenjem standardnih senzora. Razvoj displeja je međutim napredovao sporije i većina displeja koji su danas u upotrebi ima skroman dinamički opseg osvetljaja. Operator za redukciju dinamičkog opsega predstavlja ključnu komponentu sistema za reprodukciju scena širokog dinamičkog opsega (HDR), na standardnim displejima nižeg dinamičkog opsega (LDR)...Light intensity variations in natural scenes greatly exceed the capabillities of standard imaging and display devices. The human visual system has evolved to deal with these lightning conditions and enable efficient perception of details. In order to enable realistic reproduction of natural images and video, it is necessary to develop techniques and devices for capturing and reproduction of the high dynamic range content. Capturing techniques have evolved and now it is possible to capture entire dynamic range of the scene using standard sensors. The development of displays, however, has progressed more slowly and most of the displays that are used today exhibits modest dynamic range capabilities. Tone mapping operator is a key component that enables reproduction of the high dynamic range (HDR) images on the low dynamic range (LDR) displays..