Development and implementation of image fusion algorithms based on wavelets

Image fusion is a process of blending the complementary as well as the common features of a set of images, to generate a resultant image with superior information content in terms of subjective as well as objective analysis point of view. The objective of this research work is to develop some novel image fusion algorithms and their applications in various fields such as crack detection, multi spectra sensor image fusion, medical image fusion and edge detection of multi-focus images etc. The first part of this research work deals with a novel crack detection technique based on Non-Destructive Testing (NDT) for cracks in walls suppressing the diversity and complexity of wall images. It follows different edge tracking algorithms such as Hyperbolic Tangent (HBT) filtering and canny edge detection algorithm. The second part of this research work deals with a novel edge detection approach for multi-focused images by means of complex wavelets based image fusion. An illumination invariant hyperbolic tangent filter (HBT) is applied followed by an adaptive thresholding to get the real edges. The shift invariance and directionally selective diagonal filtering as well as the ease of implementation of Dual-Tree Complex Wavelet Transform (DT-CWT) ensure robust sub band fusion. It helps in avoiding the ringing artefacts that are more pronounced in Discrete Wavelet Transform (DWT). The fusion using DT-CWT also solves the problem of low contrast and blocking effects. In the third part, an improved DT-CWT based image fusion technique has been developed to compose a resultant image with better perceptual as well as quantitative image quality indices. A bilateral sharpness based weighting scheme has been implemented for the high frequency coefficients taking both gradient and its phase coherence in accoun

Seismic Applications of Interactive Computational Methods

Effective interactive computing methods are needed in a number of specific areas of geophysical interpretation, even though the basic algorithms have been established. One approach to raise the quality of interpretation is to promote better interaction between human and the computer. The thesis is concerned with improving this dialog in three areas: automatic event picking, data visualization and sparse data imaging. Fully automatic seismic event picking methods work well in relatively good conditions. They collapse when the signal-to-noise ratio is low and the structure of the subsurface is complex. The interactive seismic event picking system described here blends the interpreter's guidance and judgment into the computer program, as it can bring the user into the loop to make subjective decisions when the picking problem is complicated. Several interactive approaches for 2-D event picking and 3-D horizon tracking have been developed. Envelope (or amplitude) threshold detection for first break picking is based on the assumption that the power of the signal is larger than that of the noise. Correlation and instantaneous phase pickers are designed for and better suited to picking other arrivals. The former is based on the cross-correlation function, and a model trace (or model traces) selected by the interpreter is needed. The instantaneous phase picker is designed to track spatial variations in the instantaneous phase of the analytic form of the arrival. The picking options implemented into the software package SeisWin were tested on real data drawn from many sources, such as full waveform sonic borehole logs, seismic reflection surveys and borehole radar profiles, as well as seven of the most recent 3-D seismic surveys conducted over Australian coal mines. The results show that the interactive picking system in SeisWin is efficient and tolerant. The 3-D horizon tracking method developed especially attracts industrial users. The visualization of data is also a part of the study, as picking accuracy, and indeed the whole of seismic interpretation depends largely on the quality of the final display. The display is often the only window through which an interpreter can see the earth's substructures. Display is a non-linear operation. Adjustments made to meet display deficiencies such as automatic gain control (AGC) have an important and yet ill-documented effect on the performance of pattern recognition operators, both human and computational. AGC is usually implemented in one dimension. Some of the tools in wide spread use for two dimensional image processing which are of great value in the local gain control of conventional seismic sections such as edge detectors, histogram equalisers, high-pass filters, shaded relief are discussed. Examples are presented to show the relative effectiveness of various display options. Conventional migration requires dense arrays with uniform coverage and uniform illumination of targets. There are, however, many instances in which these ideals can not be approached. Event migration and common tangent plane stacking procedures were developed especially for sparse data sets as a part of the research effort underlying this thesis. Picked-event migration migrates the line between any two points on different traces on the time section to the base map. The interplay between the space and time domain gives the interpreter an immediate view of mapping. Tangent plane migration maps the reflector by accumulating the energy from any two possible reflecting points along the common tangent lines on the space plane. These methods have been applied to both seismic and borehole-radar data and satisfactory results have been achieved

Seismic Applications of Interactive Computational Methods

Effective interactive computing methods are needed in a number of specific areas of geophysical interpretation, even though the basic algorithms have been established. One approach to raise the quality of interpretation is to promote better interaction between human and the computer. The thesis is concerned with improving this dialog in three areas: automatic event picking, data visualization and sparse data imaging. Fully automatic seismic event picking methods work well in relatively good conditions. They collapse when the signal-to-noise ratio is low and the structure of the subsurface is complex. The interactive seismic event picking system described here blends the interpreter's guidance and judgment into the computer program, as it can bring the user into the loop to make subjective decisions when the picking problem is complicated. Several interactive approaches for 2-D event picking and 3-D horizon tracking have been developed. Envelope (or amplitude) threshold detection for first break picking is based on the assumption that the power of the signal is larger than that of the noise. Correlation and instantaneous phase pickers are designed for and better suited to picking other arrivals. The former is based on the cross-correlation function, and a model trace (or model traces) selected by the interpreter is needed. The instantaneous phase picker is designed to track spatial variations in the instantaneous phase of the analytic form of the arrival. The picking options implemented into the software package SeisWin were tested on real data drawn from many sources, such as full waveform sonic borehole logs, seismic reflection surveys and borehole radar profiles, as well as seven of the most recent 3-D seismic surveys conducted over Australian coal mines. The results show that the interactive picking system in SeisWin is efficient and tolerant. The 3-D horizon tracking method developed especially attracts industrial users. The visualization of data is also a part of the study, as picking accuracy, and indeed the whole of seismic interpretation depends largely on the quality of the final display. The display is often the only window through which an interpreter can see the earth's substructures. Display is a non-linear operation. Adjustments made to meet display deficiencies such as automatic gain control (AGC) have an important and yet ill-documented effect on the performance of pattern recognition operators, both human and computational. AGC is usually implemented in one dimension. Some of the tools in wide spread use for two dimensional image processing which are of great value in the local gain control of conventional seismic sections such as edge detectors, histogram equalisers, high-pass filters, shaded relief are discussed. Examples are presented to show the relative effectiveness of various display options. Conventional migration requires dense arrays with uniform coverage and uniform illumination of targets. There are, however, many instances in which these ideals can not be approached. Event migration and common tangent plane stacking procedures were developed especially for sparse data sets as a part of the research effort underlying this thesis. Picked-event migration migrates the line between any two points on different traces on the time section to the base map. The interplay between the space and time domain gives the interpreter an immediate view of mapping. Tangent plane migration maps the reflector by accumulating the energy from any two possible reflecting points along the common tangent lines on the space plane. These methods have been applied to both seismic and borehole-radar data and satisfactory results have been achieved

Enhancement of Single and Composite Images Based on Contourlet Transform Approach

Image enhancement is an imperative step in almost every image processing algorithms. Numerous image enhancement algorithms have been developed for gray scale images despite their absence in many applications lately. This thesis proposes hew image enhancement techniques of 8-bit single and composite digital color images. Recently, it has become evident that wavelet transforms are not necessarily best suited for images. Therefore, the enhancement approaches are based on a new 'true' two-dimensional transform called contourlet transform. The proposed enhancement techniques discussed in this thesis are developed based on the understanding of the working mechanisms of the new multiresolution property of contourlet transform. This research also investigates the effects of using different color space representations for color image enhancement applications. Based on this investigation an optimal color space is selected for both single image and composite image enhancement approaches. The objective evaluation steps show that the new method of enhancement not only superior to the commonly used transformation method (e.g. wavelet transform) but also to various spatial models (e.g. histogram equalizations). The results found are encouraging and the enhancement algorithms have proved to be more robust and reliable

Generalizable automated pixel-level structural segmentation of medical and biological data

Over the years, the rapid expansion in imaging techniques and equipments has driven the demand for more automation in handling large medical and biological data sets. A wealth of approaches have been suggested as optimal solutions for their respective imaging types. These solutions span various image resolutions, modalities and contrast (staining) mechanisms. Few approaches generalise well across multiple image types, contrasts or resolution. This thesis proposes an automated pixel-level framework that addresses 2D, 2D+t and 3D structural segmentation in a more generalizable manner, yet has enough adaptability to address a number of specific image modalities, spanning retinal funduscopy, sequential fluorescein angiography and two-photon microscopy. The pixel-level segmentation scheme involves: i ) constructing a phase-invariant orientation field of the local spatial neighbourhood; ii ) combining local feature maps with intensity-based measures in a structural patch context; iii ) using a complex supervised learning process to interpret the combination of all the elements in the patch in order to reach a classification decision. This has the advantage of transferability from retinal blood vessels in 2D to neural structures in 3D. To process the temporal components in non-standard 2D+t retinal angiography sequences, we first introduce a co-registration procedure: at the pairwise level, we combine projective RANSAC with a quadratic homography transformation to map the coordinate systems between any two frames. At the joint level, we construct a hierarchical approach in order for each individual frame to be registered to the global reference intra- and inter- sequence(s). We then take a non-training approach that searches in both the spatial neighbourhood of each pixel and the filter output across varying scales to locate and link microvascular centrelines to (sub-) pixel accuracy. In essence, this \link while extract" piece-wise segmentation approach combines the local phase-invariant orientation field information with additional local phase estimates to obtain a soft classification of the centreline (sub-) pixel locations. Unlike retinal segmentation problems where vasculature is the main focus, 3D neural segmentation requires additional exibility, allowing a variety of structures of anatomical importance yet with different geometric properties to be differentiated both from the background and against other structures. Notably, cellular structures, such as Purkinje cells, neural dendrites and interneurons, all display certain elongation along their medial axes, yet each class has a characteristic shape captured by an orientation field that distinguishes it from other structures. To take this into consideration, we introduce a 5D orientation mapping to capture these orientation properties. This mapping is incorporated into the local feature map description prior to a learning machine. Extensive performance evaluations and validation of each of the techniques presented in this thesis is carried out. For retinal fundus images, we compute Receiver Operating Characteristic (ROC) curves on existing public databases (DRIVE & STARE) to assess and compare our algorithms with other benchmark methods. For 2D+t retinal angiography sequences, we compute the error metrics ("Centreline Error") of our scheme with other benchmark methods. For microscopic cortical data stacks, we present segmentation results on both surrogate data with known ground-truth and experimental rat cerebellar cortex two-photon microscopic tissue stacks.Open Acces

Dynamic range reduction of infrared images based on adaptive equalization, stretch and compression of histogram

Рассматривается задача уменьшения динамического диапазона и улучшения качества инфракрасных (ИК) изображений с широким динамическим диапазоном для их отображения на жидкокристаллической матрице, пиксели которой имеют разрядность 8 бит. Для решения данной задачи в оптико-электронных приборах в реальном масштабе времени широко используются блочные алгоритмы на основе локального выравнивания гистограммы с учетом их относительно низкой вычислительной сложности и возможности учета локальных особенностей распределения яркости. Базовый алгоритм адаптивного выравнивания гистограммы обеспечивает достаточно высокое качество изображений после преобразования, но может приводить к чрезмерной контрастности для некоторых типов изображений. В модифицированном алгоритме адаптивного выравнивания гистограммы контраст ограничивается с помощью порога за счет усечения локальных максимумов на краях гистограммы. Однако это приводит к ухудшению других показателей качества изображения. Данный недостаток свойственен многим алгоритмам локального выравнивания гистограммы наряду с ограниченными возможностями управления характеристиками качества воспроизведения изображений. Для повышения качества и расширения интервала управления характеристиками воспроизведения ИК-изображений предложен алгоритм двойного уменьшения динамического диапазона изображения с промежуточным управлением формой его гистограммы. Данный алгоритм осуществляет предварительное уменьшение динамического диапазона изображения на основе адаптивного выравнивания гистограммы, управление формой гистограммы на основе ее линейного или нелинейного сжатия, линейного растяжения ее центральной части и линейного растяжения (сжатия) ее боковых частей, окончательное уменьшение динамического диапазона на основе линейного сжатия всей гистограммы. Проведено сравнение характеристик предложенного алгоритма с характеристиками известных алгоритмов уменьшения динамического диапазона и улучшения качества изображений. Приведены зависимости характеристик качества воспроизведения изображений после уменьшения их динамического диапазона от параметров управления предложенного алгоритма и рекомендации по их выбору с учетом вычислительной сложности. The problem of reducing the dynamic range and improving the quality of infrared (IR) images with a wide dynamic range for their display on a liquid crystal matrix with 8-bit pixels is considered. To solve this problem in optoelectronic devices in real time, block algorithms based on local equalization of the histogram are widely used, taking into account their relatively low computational complexity and the possibility of taking into account local features of the brightness distribution. The basic adaptive histogram equalization algorithm provides reasonably high image quality after conversion, but may result in excessive contrast for some types of images. In a modified algorithm of adaptive histogram equalization, the contrast is limited by a threshold by truncating local maxima at the edges of the histogram. This leads, however, to a deterioration in other indicators of image quality. This disadvantage is inherent in many algorithms of local histogram equalization, along with limited control over the characteristics of image reproduction quality. To improve the quality and expand the control interval for the characteristics of the reproduction of infrared images, the article proposes an algorithm for double reduction of the dynamic range of the image with intermediate control of the shape of its histogram. This algorithm performs: preliminary reduction of the dynamic range of the image based on adaptive equalization of the histogram, control of the shape of the histogram based on its linear or nonlinear compression, linear stretching of its central part and linear stretching (compression) of its lateral parts, final reduction of the dynamic range based on linear compression of the entire histograms. The characteristics of the proposed algorithm are compared with the characteristics of known algorithms for reducing the dynamic range and improving the image quality. The dependences of the characteristics of the quality of image reproduction after a decrease in their dynamic range on the control parameters of the proposed algorithm and recommendations for their choice taking into account the computational complexity are given

Уменьшение динамического диапазона инфракрасных изображений на основе адаптивного выравнивания, растяжения и сжатия гистограммы

The problem of reducing the dynamic range and improving the quality of infrared (IR) images with a wide dynamic range for their display on a liquid crystal matrix with 8-bit pixels is considered. To solve this problem in optoelectronic devices in real time, block algorithms based on local equalization of the histogram are widely used, taking into account their relatively low computational complexity and the possibility of taking into account local features of the brightness distribution. The basic adaptive histogram equalization algorithm provides reasonably high image quality after conversion, but may result in excessive contrast for some types of images. In a modified algorithm of adaptive histogram equalization, the contrast is limited by a threshold by truncating local maxima at the edges of the histogram. This leads, however, to a deterioration in other indicators of image quality. This disadvantage is inherent in many algorithms of local histogram equalization, along with limited control over the characteristics of image reproduction quality. To improve the quality and expand the control interval for the characteristics of the reproduction of infrared images, the article proposes an algorithm for double reduction of the dynamic range of the image with intermediate control of the shape of its histogram. This algorithm performs: preliminary reduction of the dynamic range of the image based on adaptive equalization of the histogram, control of the shape of the histogram based on its linear or nonlinear compression, linear stretching of its central part and linear stretching (compression) of its lateral parts, final reduction of the dynamic range based on linear compression of the entire histograms. The characteristics of the proposed algorithm are compared with the characteristics of known algorithms for reducing the dynamic range and improving the image quality. The dependences of the characteristics of the quality of image reproduction after a decrease in their dynamic range on the control parameters of the proposed algorithm and recommendations for their choice taking into account the computational complexity are given.Рассматривается задача уменьшения динамического диапазона и улучшения качества инфракрасных (ИК) изображений с широким динамическим диапазоном для их отображения на жидкокристаллической матрице, пиксели которой имеют разрядность 8 бит. Для решения данной задачи в оптико-электронных приборах в реальном масштабе времени широко используются блочные алгоритмы на основе локального выравнивания гистограммы с учетом их относительно низкой вычислительной сложности и возможности учета локальных особенностей распределения яркости. Базовый алгоритм адаптивного выравнивания гистограммы обеспечивает достаточно высокое качество изображений после преобразования, но может приводить к чрезмерной контрастности для некоторых типов изображений. В модифицированном алгоритме адаптивного выравнивания гистограммы контраст ограничивается с помощью порога за счет усечения локальных максимумов на краях гистограммы. Однако это приводит к ухудшению других показателей качества изображения. Данный недостаток свойственен многим алгоритмам локального выравнивания гистограммы наряду с ограниченными возможностями управления характеристиками качества воспроизведения изображений. Для повышения качества и расширения интервала управления характеристиками воспроизведения ИК-изображений предложен алгоритм двойного уменьшения динамического диапазона изображения с промежуточным управлением формой его гистограммы. Данный алгоритм осуществляет предварительное уменьшение динамического диапазона изображения на основе адаптивного выравнивания гистограммы, управление формой гистограммы на основе ее линейного или нелинейного сжатия, линейного растяжения ее центральной части и линейного растяжения (сжатия) ее боковых частей, окончательное уменьшение динамического диапазона на основе линейного сжатия всей гистограммы. Проведено сравнение характеристик предложенного алгоритма с характеристиками известных алгоритмов уменьшения динамического диапазона и улучшения качества изображений. Приведены зависимости характеристик качества воспроизведения изображений после уменьшения их динамического диапазона от параметров управления предложенного алгоритма и рекомендации по их выбору с учетом вычислительной сложности