Today, infrared cameras are used especially for target tracking and surveillance operations. However, they have a high dynamic range output, and the standard display devices cannot handle them. In order to show them on common devices, the dynamic range is cropped. Thus, the contrast of the image is reduced. This is called as the High Dynamic Range (HDR) Compression. Although several algorithms have been proposed for preserving details during the HDR compression process, it cannot be used to enhance the local contrasts of image contents. In this thesis, we compare the performances of contrast enhancement techniques, which are suitable for real time applications. The methods experimented are generally histogram based methods. Some modifications are also proposed in order to reduce computational complexity of the process. Performances of these methods are compared with common objective quality metrics on different image sets.

The performance, reliability, and ubiquity of automatic speech recognition systems has flourished in recent years due to steadily increasing computational power and technological innovations such as hidden Markov models, weighted finite-state transducers, and deep learning methods. One problem which plagues speech recognition systems, especially those that operate offline and have been trained on specific in-domain data, is the deleterious effect of noise on the accuracy of speech recognition. Historically, robust speech recognition research has focused on traditional noise types such as additive noise, linear filtering, and reverberation. This thesis describes the effects of nonlinear dynamic range compression on automatic speech recognition and develops a number of novel techniques for characterizing and counteracting it. Dynamic range compression is any function which reduces the dynamic range of an input signal. Dynamic range compression is a widely-used tool in audio engineering and is almost always a component of a practical telecommunications system. Despite its ubiquity, this thesis is the first work to comprehensively study and address the effect of dynamic range compression on speech recognition. More specifically, this thesis treats the problem of dynamic range compression in three ways: (1) blind amplitude normalization methods, which counteract dynamic range compression when its parameter values allow the function to be mathematically inverted, (2) blind amplitude reconstruction techniques, i.e., declipping, which attempt to reconstruct clipped segments of the speech signal that are lost through non-invertible dynamic range compression, and (3) matched-training techniques, which attempt to select the pre-trained acoustic model with the closest set of compression parameters. All three of these methods rely on robust estimation of the dynamic range compression distortion parameters. Novel algorithms for the blind prediction of these parameters are also introduced. The algorithms' quality is evaluated in terms of the degree to which they decrease speech recognition word error rate, as well as in terms of the degree to which they increase a given speech signal's signal-to-noise ratio. In all evaluations, the possibility of independent additive noise following the application of dynamic range compression is assumed.

The aim of the thesis is to create a digital equalizer with dynamic range compression. The master's thesis is focused on the comparison of functions and parameters of individual digital processors which are given entirely for sound signals processing. It contains the detailed analysis of singular blocks used for signal processing in the circuit AD1953 and possibilities of control over programmable parametres of those blocks by a user. This thesis also contains a comparasion of the chosen A/D converters together with a description of the UDA1361TS circuit. A designed functional diagram of the final device is introduced as well. Thereafter possibilities of controling the individual blocks in the signal processor are mentioned. The final design of the digital equalizer is also introduced along with a description of software essential to a successful control over the processing of the signal in the AD1953 circuit. This thesis also describes a construction of the digital equalizer and involves results of the chosen measurements.

This thesis concerns with the introduction to the problematics of images with high dynamic range (HDR) and possibilities of HDR images compression options for display on devices with a low dynamic range (LDR). In the introduction is described historical evolution of recording of reality. It is focusing towards point of view of physics, human visual perception and digital recording. There are described the ways of generating and holding of HDR images. The thesis is corncerned to the techniques of HDR compression, it means the tone-mapping. The different techniques of tone-mapping are explained and specific aproach is targeted to the gradient domain high dynamic range compresion.

This work deals with the problem of reverse audio engineering for active listening. The format under consideration corresponds to the audio CD. The musical content is viewed as the result of a concatenation of the composition, the recording, the mixing, and the mastering. The inversion of the two latter stages constitutes the core of the problem at hand. The audio signal is treated as a post-nonlinear mixture. Thus, the mixture is "decompressed" before being "decomposed" into audio tracks. The problem is tackled in an informed context: The inversion is accompanied by information which is specific to the content production. In this manner, the quality of the inversion is significantly improved. The information is reduced in size by the use of quantification and coding methods, and some facts on psychoacoustics. The proposed methods are applicable in real time and have a low complexity. The obtained results advance the state of the art and contribute new insights.

Ce travail s’intéresse au problème de la rétroingénierie du son pour l’écoute active. Le format considéré correspond au CD audio. Le contenu musical est vu comme le résultat d’un enchaînement de la composition, l’enregistrement, le mixage et le mastering. L’inversion des deux dernières étapes constitue le fond du problème présent. Le signal audio est traité comme un mélange post-non-linéaire. Ainsi, le mélange est « décompressé » avant d'être « décomposé » en pistes audio. Le problème est abordé dans un contexte informé : l’inversion est accompagnée d'une information qui est spécifique à la production du contenu. De cette manière, la qualité de l’inversion est significativement améliorée. L’information est réduite de taille en se servant des méthodes de quantification, codage, et des faits sur la psychoacoustique. Les méthodes proposées s’appliquent en temps réel et montrent une complexité basse. Les résultats obtenus améliorent l’état de l’art et contribuent aux nouvelles connaissances. / This work deals with the problem of reverse audio engineering for active listening. The format under consideration corresponds to the audio CD. The musical content is viewed as the result of a concatenation of the composition, the recording, the mixing, and the mastering. The inversion of the two latter stages constitutes the core of the problem at hand. The audio signal is treated as a post-nonlinear mixture. Thus, the mixture is “decompressed” before being “decomposed” into audio tracks. The problem is tackled in an informed context: The inversion is accompanied by information which is specific to the content production. In this manner, the quality of the inversion is significantly improved. The information is reduced in size by the use of quantification and coding methods, and some facts on psychoacoustics. The proposed methods are applicable in real time and have a low complexity. The obtained results advance the state of the art and contribute new insights.

This thesis focuses on the high dynamic range (HDR) imaging problematic. It describes process of capturing and storage of HDR images in brief. Main part of thesis deals with techniques of how to display HDR images on common visual display devices, which are not able to represent them directly. This process is called tone-mapping. It is firstly described in general and than the text focuses on several techniques of tone-mapping, mainly on tone-mapping using bilateral filtering.

Sound localization is a vital aspect of hearing for safe navigation of everyday environments. It is also an important factor in speech intelligibility. This ability is facilitated by the interaural level difference (ILD) cue, which arises from binaural hearing: a sound will be more intense at the nearer ear than the farther. In a hearing-impaired listener, this binaural cue may not be available for use and localization may be diminished. While conventional, bilateral, wide dynamic range compression (WDRC) hearing aids distort the interaural level difference by independently altering sound intensities in each ear, wirelessly-linked devices have been suggested to benefit this task by matching amplification in order to preserve ILD. However, this technology has been shown to have varying degrees of success in aiding speech intelligibility and sound localization. As hearing impairment has wide-ranging adverse impacts to physical and mental health, social activity, and cognition, the task of localization improvement must be urgently addressed. Toward this end, neural modelling techniques are used to determine neural representations of ILD cues for linked and unlinked bilateral WDRC hearing aids. Findings suggest that wirelessly-linked WDRC is preferable over unlinked hearing aids or unaided, hearing-impaired listening, although parameters for optimal benefit are dependent on sound level, frequency content, and preceding sounds. / Thesis / Master of Applied Science (MASc)