Vector Ordering and Morphological Operations for Colour Image Processing: Fundamentals and Applications

: The extension of concepts of greyscale morphology to colour image processing requires the use of a proper ordering of vectors (colours) and the definitions of infimum and supremum operators in an appropriate colour space. In this paper, a new approach to colour image morphology is proposed. It is based on a new ordering of vectors in the HSV colour space that is partial ordering. The proposed approach is hue preserving, and it is not a component-wise technique. Its basic characteristic is that it is compatible to the standard greyscale morphology: its fundamental and secondary operations possess the same basic properties as their greyscale counterparts, and furthermore, it is identical to greyscale morphology when it is applied to greyscale images. Examples that illustrate the application of the defined operations to colour images are provided. Moreover, the usefulness of the new method in various colour image processing applications, such as colour image edge detection, object recognition, vector top-hat filtering and skeleton extraction, is demonstrated. Received: 14 July 2000, Received in revised form: 24 April 2001, Accepted: 19 June 2001     

Natural colour mapping for multiband nightvision imagery

We present a method to give (fused) multiband night-time imagery a natural day-time colour appearance. For input, the method requires a false colour RGB image that is produced by mapping three individual bands (or the first three principal components) of a multiband nightvision system to the respective channels of an RGB image. The false colour RGB nightvision image is transformed into a perceptually decorrelated colour space. In this colour space the first order statistics of a natural colour image (target scene) are transferred to the multiband nightvision image (source scene). To obtain a natural colour representation of the multiband night-time imagery, the compositions of the source and target scenes should resemble each other to some degree. The inverse transformation to RGB space yields a nightvision image with a day-time colour appearance. The luminance contrast of the resulting colour image can be enhanced by replacing its luminance component by a grayscale fused representation of the three input bands.     

A new universal colour image fidelity metric

We extend a recently introduced universal grayscale image quality index to a newly developed perceptually decorrelated colour space. The resulting colour image fidelity metric quantifies the distortion of a processed colour image relative to its original version. We evaluated the new colour image fidelity metric through observer experiments in which subjects ranked images according to perceived distortion. The metric correlates strongly with human perception and can therefore be used to assess the performance of colour image coding and compression schemes, colour image enhancement algorithms, synthetic colour image generators, and colour image fusion schemes.     

Optical Image Processing Using Light Modulation Displays

We propose to enhance the capabilities of the human visual system by performing optical image processing directly on an observed scene. Unlike previous work which additively superimposes imagery on a scene, or completely replaces scene imagery with a manipulated version, we perform all manipulation through the use of a light modulation display to spatially filter incoming light. We demonstrate a number of perceptually motivated algorithms including contrast enhancement and reduction, object highlighting for preattentive emphasis, colour saturation, de‐saturation and de‐metamerization, as well as visual enhancement for the colour blind. A camera observing the scene guides the algorithms for on‐the‐fly processing, enabling dynamic application scenarios such as monocular scopes, eyeglasses and windshields.     

Perceptual correction for colour grading of random textures

We present a method of colour shade grading for industrial inspection of random textures, the differences of which are at the threshold of human perception. This method uses image restoration techniques to recover an unblurred version of the image, and then blurs it the same way as the human visual system does, to emulate the process of the image being captured by the human sensor. Subsequently, the colour image is transformed into a perceptually uniform colour space, where colour gra ding takes place. Received: 10 October 1998 / Accepted: 21 March 2000     

Colour image compression based on the measure of just noticeable colour difference

To the human vision, there exists in colour images a certain amount of perceptual redundancy since the human visual system (HVS) has limited sensitivity in discriminating colour signals of small differences. By measuring the perceptual redundancy inherent in colour images and shaping the coding distortion into the perceptual redundancy, colour images are expected to be represented more efficiently. Approaches to perceptually optimise the efficiency of image coders in compressing colour images with the perceptual redundancy estimated by a colour visual model are presented. The model estimates the perceptual redundancy for each colour pixel as a visibility threshold of colour difference in any colour space and in a spatial or frequency domain. Two existing image coders are modified to take advantage of the perceptual redundancy and simulated to inspect if their coding efficiency is improved. In the spatial domain, the JPEG-LS coder in the near-lossless compression mode is modified to make coding errors part of the perceptual redundancy in compressing colour images in the RGB space. In the wavelet domain, the JPEG2000 coder is refined by minimising the perceptible distortion involved in the rate control of the compressed image in the YC/sub b/C/sub r/space. Simulation results show that, in both cases, the performance of the perceptually tuned coder is superior to that of the un-tuned coder in terms of the bit rate required for achieving the same visual quality.     

A perceptually optimized mapping technique for display images

Liquid crystal displays (LCDs) are often viewed in the energy‐saving mode or under high ambient illumination. However, both these conditions compress the tonal dynamic range of the display device, resulting in undesirable visual perception effects. In this paper, we propose a local algorithm for improving the display image quality under either of these conditions. The proposed algorithm is based on a tone mapping technique, and it reproduces the image appearance to almost its original quality with a lower dynamic range. We also develop a more accurate definition of the image distortion, which takes into account the difference in pixel values to reduce the distortion significantly. By minimizing the differences in contrast and pixel intensity between the input and output images, the algorithm preserves the contrast while simultaneously providing brightness compensation. Simulation results show that the proposed algorithm can effectively maintain image quality while enabling power savings of 30%–50%.     

Soft Morphological Filtering Using a Fuzzy Model and its Application to Colour Image Processing

Abstract Soft morphological filters form a class of filters with many desirable properties. They were introduced to improve the behaviour of standard morphological filters in detail preservation and noise elimination. In this paper, a framework for soft morphological colour image processing using a fuzzy model is introduced. This extends the standard colour morphological operators in the same way that soft greyscale morphology extends the standard greyscale morphology theory. The primary and secondary operations of the new soft morphological approach are defined. The proposed operators are less sensitive to image distortion and to small variations in the shape of the objects, and perform significantly better in impulse noise removal problems, compared to standard morphological operators. Experimental results of the application to real colour images demonstrate these advantageous characteristics of the new operators. Additionally, illustrative examples that exhibit the applicability of the proposed methodology to edge detection problems are also included.An erratum to this article can be found at     

Robust and transparent watermarking scheme for colour images

In this study, a robust and transparent watermarking scheme for colour images is proposed. The colour features for the human visual system are utilised to design the colour watermarking scheme. Through the exploitation of the perceptual redundancy of colour images, the proposed watermarking scheme is perceptually tuned to embed and detect the watermark in the perceptually significant sub-bands of luminance and chrominance components of colour images in the wavelet domain. The employment of the uniformity in the uniform colour space and the masking effect mainly due to local variations in luminance magnitude leads to that the perceptual redundancy of colour images can be measured. By using the estimated perceptual redundancy in the form of error visibility thresholds of wavelet coefficients of the colour image, high strength watermarks are invisibly embedded into coefficients of the host colour image for resisting compression and malicious attacks. Simulation results show that the estimation of perceptual redundancy is helpful to the design of the watermarking scheme for colour images. The performance in terms of robustness and transparency of the proposed watermarking scheme is superior to that of the existing scheme.     

Perceptually Based Appearance Modification for Compliant Appearance Editing

Projection‐based appearances are used in a variety of computer graphics applications to impart different appearances onto physical surfaces using digitally controlled projector light. To achieve a compliant appearance, all points on the physical surface must be altered to the colours of the desired target appearance; otherwise, an incompliant appearance results in a misleading visualization. Previous systems typically assume to operate with compliant appearances or restrict themselves to the simpler case of white surfaces. To achieve compliancy, one may change the physical surface's albedo, increase the amount of projector light radiance available or modify the target appearance's colours. This paper presents an approach to modify a target appearance to achieve compliant appearance editing without altering the physical surface or the projector setup. Our system minimally alters the target appearance's colours while maintaining cues important for perceptual similarity (e.g. colour constancy). First, we discuss how to measure colour compliancy. Next, we describe our approach to partition the physical surface into patches based on the surface's colours and the target appearance's colours. Finally, we describe our appearance optimization process, which computes a compliant appearance that is as perceptually similar as possible to the target appearance's colours. We perform several real‐world projection‐based appearances and compare our results to naïve approaches, which either ignore compliancy or simply reduce the appearance's overall brightness.     

Multispectral image fusion for improved RGB representation based on perceptual attributes

A pixel‐level fusion technique for RGB representation of multispectral images is proposed. The technique results in highly correlated RGB components, a fact which occurs in natural colour images and is strictly related to the colour perception attributes of the human eye. Accordingly, specific properties for the covariance matrix of the final RGB image are demanded. Mutual information is employed as an objective criterion for quality refinement. The method provides dimensionality reduction, while the resulting RGB colour image is perceptually of high quality. Comparisons with existing techniques are carried out using both subjective and objective measures.     

Multispectral image segmentation by a multichannel watershed‐based approach

Watershed transformation in mathematical morphology is a powerful morphological tool for image segmentation that is usually defined for greyscale images and applied to the gradient magnitude of an image. This paper presents an extension of the watershed algorithm for multispectral image segmentation. A vector‐based morphological approach is proposed to compute gradient magnitude from multispectral imagery, which is then input into watershed transformation for image segmentation. The gradient magnitude is obtained at multiple scales. After an automatic elimination of local irrelevant minima, a watershed transformation is applied to segment the image. The segmentation results were evaluated and compared with other multispectral image segmentation methods, in terms of visual inspection, and object‐based image classification using high resolution multispectral images. The experimental results indicate that the proposed method can produce accurate segmentation results and higher classification accuracy, if the scales and contrast parameter are appropriately selected in the gradient computation and subsequent local minima elimination. The proposed method shows encouraging results and can be used for segmentation of high resolution multispectral imagery and object based classification.     

数字图像处理中通道原理及应用的研究

从通道与色彩的关系出发,将通道分为3种类型：原色通道、Alpha通道和专色通道,并通过实例深入剖析了通道的原理,指出通道的实质就是灰度图,灰度图中每一个像素均代表着图像中相同位置的像素,灰度的明暗反映了图像的颜色信息,举例说明了通道在调整图像颜色和保存、载入图像方面的应用。     

Adaptive Image‐Space Sampling for Gaze‐Contingent Real‐time Rendering

With ever‐increasing display resolution for wide field‐of‐view displays—such as head‐mounted displays or 8k projectors—shading has become the major computational cost in rasterization. To reduce computational effort, we propose an algorithm that only shades visible features of the image while cost‐effectively interpolating the remaining features without affecting perceived quality. In contrast to previous approaches we do not only simulate acuity falloff but also introduce a sampling scheme that incorporates multiple aspects of the human visual system: acuity, eye motion, contrast (stemming from geometry, material or lighting properties), and brightness adaptation. Our sampling scheme is incorporated into a deferred shading pipeline to shade the image's perceptually relevant fragments while a pull‐push algorithm interpolates the radiance for the rest of the image. Our approach does not impose any restrictions on the performed shading. We conduct a number of psycho‐visual experiments to validate scene‐ and task‐independence of our approach. The number of fragments that need to be shaded is reduced by 50 % to 80 %. Our algorithm scales favorably with increasing resolution and field‐of‐view, rendering it well‐suited for head‐mounted displays and wide‐field‐of‐view projection.     

Colour Mathematical Morphology For Neural Image Analysis

This paper presents an algorithm for automatic neural image analysis in immunostained vertebrate retinas. We present a useful tool for cell quantification avoiding the losst of information of traditional binary techniques in automatic recognition of images. The application is based on the extension of the mathematical morphology to colour images. In qthe paper, we define the basics and more complex morphological operations to vectorial image processing. We propose and demonstrate a colour image reconstruction by geodesic transformations. In addition, we adapt the morphological segmentation of greyscale image to the segmentation of multispectral images of retinas of monkeys.     

Spatialization design: comparing points and landscapes

Spatializations represent non-spatial data using a spatial layout similar to a map. We present an experiment comparing different visual representations of spatialized data, to determine which representations are best for a non-trivial search and point estimation task. Primarily, we compare point-based displays to 2D and 3D information landscapes. We also compare a colour (hue) scale to a grey (lightness) scale. For the task we studied, point-based spatializations were far superior to landscapes, and 2D landscapes were superior to 3D landscapes. Little or no benefit was found for redundantly encoding data using colour or greyscale combined with landscape height. 3D landscapes with no colour scale (height-only) were particularly slow and inaccurate. A colour scale was found to be better than a greyscale for all display types, but a greyscale was helpful compared to height-only. These results suggest that point-based spatializations should be chosen over landscape representations, at least for tasks involving only point data itself rather than derived information about the data space.     

Image Contrast Enhancement by Constrained Local Histogram Equalization

Histogram equalization is a widely used image contrast enhancement method. While global histogram equalization enhances the contrast of the whole image, local histogram equalization can enhance many image details by taking different transformation of the same gray level at different places in the original image. However, the local histogram equalization process often results in unacceptable modification of the original image appearance. In this paper, a constrained local histogram equalization method is proposed to balance the conflicting requirements: enhancement of the image details and the maintenance of the overall image appearance. Our method uses the variational form of histogram equalization so that a constraint condition, which forces the local gray level transformations to change continuously in the spatial domain, can be introduced into the equalization process. Experimental results of different kinds of images show the effect of our method.     

Illuminant and device invariant colour using histogram equalisation

Colour can potentially provide useful information for a variety of computer vision tasks such as image segmentation, image retrieval, object recognition and tracking. However, for it to be helpful in practice, colour must relate directly to the intrinsic properties of the imaged objects and be independent of imaging conditions such as scene illumination and the imaging device. To this end many invariant colour representations have been proposed in the literature. Unfortunately, recent work (Second Workshop on Content-based Multimedia Indexing) has shown that none of them provides good enough practical performance.In this paper we propose a new colour invariant image representation based on an existing grey-scale image enhancement technique: histogram equalisation. We show that provided the rank ordering of sensor responses are preserved across a change in imaging conditions (lighting or device) a histogram equalisation of each channel of a colour image renders it invariant to these conditions. We set out theoretical conditions under which rank ordering of sensor responses is preserved and we present empirical evidence which demonstrates that rank ordering is maintained in practice for a wide range of illuminants and imaging devices. Finally, we apply the method to an image indexing application and show that the method out performs all previous invariant representations, giving close to perfect illumination invariance and very good performance across a change in device.