Image enhancement in wavelet domain based on histogram equalization and median filter

During the acquisition of a new digital image, noise may be introduced as a result of the production process. Image enhancement is used to alleviate problems caused by noise. In this work, the purpose is to propose, apply, and evaluate enhancement approaches to images by selecting suitable filters to produce improved quality and performance results. The new method proposed for image noise reduction as an enhancement process employs threshold and histogram equalization implemented in the wavelet domain. Different types of wavelet filters were tested to obtain the best results for the image noise reduction process. Also, the effect of canceling one or more of the high-frequency bands in the wavelet domain was tested. The mean square error and peak signal to noise ratio are used for measuring the improvement in image noise reduction. A comparison made with two related works shows the superiority of the methods proposed and implemented in this research. The proposed methods of applying the median filter before and after the histogram equalization methods produce improvement in performance and efficiency compared to the case of using discrete wavelet transform only, even with the cases of multiresolution discrete wavelet transform and the cancellation step

An Algorithm on Generalized Un Sharp Masking for Sharpness and Contrast of an Exploratory Data Model

In the applications like medical radiography enhancing movie features and observing the planets it is necessary to enhance the contrast and sharpness of an image. The model proposes a generalized unsharp masking algorithm using the exploratory data model as a unified framework. The proposed algorithm is designed as to solve simultaneously enhancing contrast and sharpness by means of individual treatment of the model component and the residual, reducing the halo effect by means of an edge-preserving filter, solving the out of range problem by means of log ratio and tangent operations. Here is a new system called the tangent system which is based upon a specific bargeman divergence. Experimental results show that the proposed algorithm is able to significantly improve the contrast and sharpness of an image. Using this algorithm user can adjust the two parameters the contrast and sharpness to have desired output

Histogram equalization for robust text-independent speaker verification in telephone environments

Word processed copy. Includes bibliographical references

Reviewing the Effectivity Factor in Existing Techniques of Image Forensics

Studies towards image forensics are about a decade old and various forms of research techniques have been presented till date towards image forgery detection. Majority of the existing techniques deals with identification of tampered regions using different forms of research methodologies. However, it is still an open-end question about the effectiveness of existing image forgery detection techniques as there is no reported benchmarked outcome till date about it. Therefore, the present manuscript discusses about the most frequently addressed image attacks e.g. image splicing and copy-move attack and elaborates the existing techniques presented by research community to resist it. The paper also contributes to explore the direction of present research trend with respect to tool adoption, database adoption, and technique adoption, and frequently used attack scenario. Finally, significant open research gap are explored after reviewing effectiveness of existing techniques

A robust version of the Lee filter for speckle reduction and contrast enhancement applied to side scan sonar images

Sonar images are typically affected by a granular pattern interference known as speckle noise, which degrades image contrast. To aid in object detection and recognition for speckled imagery, a robust version of the Lee filter is presented. The new method essentially combines robust statistics with an adaptive approach to achieve an effective balance between contrast stretching and speckle reduction. Tests were performed on real sonar images, where objective metrics and direct visual perception were used to evaluate the results. Experiments have shown that this easy-to-implement filter remarkably highlights edges and details with apparent speckle reduction, offering a promising simple tool that may be useful in segmentation and classification applications.Publicado en: 2020 IEEE Congreso Bienal de Argentina (ARGENCON

The feasability of implementing a face recognition system based on Gabor filter and nearst nighbour techniques in an FPGA device for door control systems

Door access control systems based on face recognition are geared towards simplifying difficult face recognition problems in uncontrolled environments. Such systems are able to control illumination, offer neutral pose and improve the poor performance of many face recognition algorithms. Door access control systems control illumination and pose in order to overcome face recognition problems. While there have been significant improvements in the algorithms with increasing recognition accuracy, very little research has been conducted on implementing these in hardware devices. Most of the previous studies focused on implementing a simple principal component analysis in hardware with low recognition accuracy. In contrast, the use of a Gabor filter for feature extraction and the nearest neighbour method for classification were found to be better alternatives. Dramatic developments in field programmable gate arrays (FPGAs) have allowed designers to select various resources and functions to implement many complex designs. The aim of this paper is to present the feasibility of implementing Gabor filter and nearest neighbour face recognition algorithms in an FPGA device for face recognition. Our simulation using Xilinx FPGA platforms verified the feasibility of such a system with minimum hardware requirements

Advanced performance monitoring in all-optical networks.

This thesis investigates advanced optical performance monitoring approaches for future all-optical networks using the synchronous sampling technique. This allows for improved signal quality estimation, fault management and resource allocation through improved control of transmission at the physical layer level. Because of the increased transparency in next generation networks, it is not possible to verify the quality of the signal at each node because of the limited number of optical-electrical-optical conversions, and therefore new non-intrusive mechanisms to achieve signal quality monitoring are needed. The synchronous sampling technique can be deployed to estimate the bit error rate, considered an important quality measure, and hence can be utilised to certify service level agreements between operators and customers. This method also has fault identification capabilities by analysing the shapes of the obtained histograms. Each impairment affects the histogram in a specific way, giving it a unique shape that can be used for root cause analysis. However, chromatic dispersion and polarisation mode dispersion (PMD) can have similar signatures on the histograms obtained at decision times. A novel technique to unambiguously discriminate between these two sources of degradation is proposed in this work. It consists of varying the decision times so that sampling also occurs at both edges of the eye diagram. This approach is referred to as three-section eye sampling technique. In addition, it is shown that this method can be used to accurately assess first order polarisation mode dispersion and can simultaneously estimate the differential group delay (DGD) and the power splitting ratio between the two states of polarisation. Since synchronous sampling is employed, the effect of PMD on the sampling times is also investigated. For the first time, closed form relationship between the shift in sampling time, the DGD and the power splitting ratio between the polarisation states is obtained. Three types of high-Q filter based clock recovery circuits are considered: without pre-processing circuits that can be used for RZ format and with an edge detector or a squarer pre-processing circuits suitable for NRZ format. Moreover, this technique can be used to monitor chromatic dispersion and a large monitoring range of more than 1750ps/nm is experimentally demonstrated at 10Gbit/s. Since it can monitor PMD and dispersion, this method can be deployed to control dynamic PMD or dispersion compensators. Furthermore, this technique offers easy and quick inline eye mask testing and timing jitter assessment

Mathematische morfologie in de beeldverwerking Mathematical Morphology in Image Processing

Het verwerken van een afbeelding met de computer laat ons toe de kwaliteit van dit beeld te verbeteren, specifieke objecten uit het beeld te segmenteren, of extra informatie tevoorschijn te halen. Mathematische morfologie is een set van wiskundige technieken uit de beeldverwerking die ons toelaat (de vormen in) beelden te analyseren. Dit proefschrift levert oplossingen voor een aantal problemen uit de beeldverwerking, met behulp van mathematische morfologie. Morfologie toepassen op zwart-wit- of grijswaardenbeelden is relatief eenvoudig, maar de theorie uitbreiden voor kleurbeelden stelt een aantal problemen. Aangezien een kleurbeeld veel meer nuttige informatie kan bevatten dan een grijswaardenbeeld, is zo'n uitbreiding wenselijk. We stellen het meerderheidsordeningsschema (MSS) voor, wat ons toelaat kleuren onderling te ordenen op een logische manier. Morfologische beeldverwerking met kleuren wordt dan mogelijk. Een ander onderzoek betreft polymeren en composieten. Deze materialen worden als glijlagers gebruikt in allerhande voorwerpen, zoals huishoudtoestellen, sluizen, poorten, etc. Vandaar dat de studie van de slijtage hiervan belangrijk is. We gaan na of het morfologische patroonspectrum, alsook vergelijkbare technieken, een bijdrage kan leveren aan het wrijvingsonderzoek van dergelijke materialen. Dit zou de snelheid en efficiëntie van de analyses kunnen verbeteren. We merken op dat de spectrale parameters interessante verbanden vertonen met de parameters van de proefopstelling. Het derde luik van de thesis betreft het ontwikkelen van een interpolatietechniek voor zwart-wit-beelden, gebaseerd op mathematische morfologie, genaamd mmINT. Interpolatie is nodig wanneer we wensen in te zoomen op een beeld of de resolutie van het beeld willen vergroten. Dit kan van pas komen wanneer we ingescande of gedownloade tekeningen van slechte kwaliteit (te lage resolutie) willen verbeteren. mmINT werkt aanzienlijk beter dan bestaande methodes. We ontwikkelden ook een snelle variant, mmINTone, en een uitbreiding voor grijswaardenbeelden, mmINTg

Advanced receivers for distributed cooperation in mobile ad hoc networks

Mobile ad hoc networks (MANETs) are rapidly deployable wireless communications systems, operating with minimal coordination in order to avoid spectral efficiency losses caused by overhead. Cooperative transmission schemes are attractive for MANETs, but the distributed nature of such protocols comes with an increased level of interference, whose impact is further amplified by the need to push the limits of energy and spectral efficiency. Hence, the impact of interference has to be mitigated through with the use PHY layer signal processing algorithms with reasonable computational complexity. Recent advances in iterative digital receiver design techniques exploit approximate Bayesian inference and derivative message passing techniques to improve the capabilities of well-established turbo detectors. In particular, expectation propagation (EP) is a flexible technique which offers attractive complexity-performance trade-offs in situations where conventional belief propagation is limited by computational complexity. Moreover, thanks to emerging techniques in deep learning, such iterative structures are cast into deep detection networks, where learning the algorithmic hyper-parameters further improves receiver performance. In this thesis, EP-based finite-impulse response decision feedback equalizers are designed, and they achieve significant improvements, especially in high spectral efficiency applications, over more conventional turbo-equalization techniques, while having the advantage of being asymptotically predictable. A framework for designing frequency-domain EP-based receivers is proposed, in order to obtain detection architectures with low computational complexity. This framework is theoretically and numerically analysed with a focus on channel equalization, and then it is also extended to handle detection for time-varying channels and multiple-antenna systems. The design of multiple-user detectors and the impact of channel estimation are also explored to understand the capabilities and limits of this framework. Finally, a finite-length performance prediction method is presented for carrying out link abstraction for the EP-based frequency domain equalizer. The impact of accurate physical layer modelling is evaluated in the context of cooperative broadcasting in tactical MANETs, thanks to a flexible MAC-level simulato