|
|
Compression and Quality Assessment of ECG Signals
Němcová, Andrea ; Tkacz,, Professor Ewaryst (referee) ; Kudrna,, Petr (referee) ; Vítek, Martin (advisor)
Ztrátová komprese signálů EKG je užitečná a v současnosti stále se rozvíjející oblast. Stále se vyvíjí nové a nové kompresní algoritmy. V této oblasti ale chybí standardy pro hodnocení kvality signálu po kompresi. Existuje tedy sice mnoho různých kompresních algoritmů, které ale buď nelze objektivně porovnat vůbec, nebo jen zhruba. V oblasti komprese navíc nikde není popsáno, zda mají na výkon kompresních algoritmů vliv patologie, popřípadě jaký. Tato dizertační práce poskytuje přehled všech nalezených metod pro hodnocení kvality signálů EKG po kompresi. Navíc bylo vytvořeno 10 nových metod. V rámci práce byla provedena analýza všech těchto metod a na základě jejích výsledků bylo doporučeno 12 metod vhodných pro hodnocení kvality signálu EKG po kompresi. Také je zde představen nový kompresní algoritmus „Single-Cycle Fractal-Based (SCyF)“. Algoritmus SCyF je inspirován metodou založenou na fraktálech a využívá jednoho cyklu signálu EKG jako domény. Algoritmus SCyF byl testován na čtyřech různých databázích, přičemž kvalita signálů po kompresi byla vyhodnocena 12 doporučenými metodami. Výsledky byly porovnány s velmi populárním kompresním algoritmem založeným na vlnkové transformaci, který využívá metodu „Set Partitioning in Hierarchical Trees (SPIHT)“. Postup testování zároveň slouží jako příklad, jak by měl vypadat standard hodnocení výkonu kompresních algoritmů. Dále bylo statisticky prokázáno, že existuje rozdíl mezi kompresí fyziologických a patologických signálů. Patologické signály byly komprimovány s nižší efektivitou a kvalitou než signály fyziologické.
|
|
|
Videocodec - Videosequence Compression
Bařina, David ; Motlíček, Petr (referee) ; Smrž, Pavel (advisor)
This thesis deals with modern methods of a lossy still image and video compression. Wavelet transformation and SPIHT algorithm also belong to these methods. In second half of this thesis, a videocodec is implemented based on acquired knowledge. This codec uses Daubechies wavelets to analyse an image. Afterwards there is a modified SPIHT algorithm applied on gained coefficients. A lot of effort was put in order to optimize this computation. It is possible to use the created codec in Video for Windows, DirectShow and FFmpeg multimedia frameworks. At the end of this thesis, commonly used codecs are compared with newly created one.
|
|
|
Compression of ECG signal
Blaschová, Eliška ; Němcová, Andrea (referee) ; Vítek, Martin (advisor)
This paper represents the most well-known compression methods, which have been published. A Compression of ECG signal is important primarily for space saving in memory cards or efficiency improvement of data transfer. An application of wavelet transform for compression is a worldwide discussed topic and this is the reason why the paper focuses in this direction. Gained wavelet coefficients might be firstly quantized and then compressed using suitable method. There are many options for a selection of wavelet and a degree of decomposition, which will be tested from the point of view of the most efficient compression of ECG signal.
|
|
|
Image Compression Using the Wavelet Transform
Kaše, David ; Klíma, Ondřej (referee) ; Bařina, David (advisor)
This thesis deals with image compression using wavelet, contourlet and shearlet transformation. It starts with quick look at image compression problem a quality measurement. Next are presented basic concepts of wavelets, multiresolution analysis and scaling function and detailed look at each transform. Representatives of algorithms for coeficients coding are EZW, SPIHT and marginally EBCOT. In second part is described design and implementation of constructed library. Last part compare result of transforms with format JPEG 2000. Comparison resulted in determining type of image in which implemented contourlet and shearlet transform were more effective than wavelet. Format JPEG 2000 was not exceeded.
|
|
|
ECG Signal Compression Based on Wavelet Transform
Ondra, Josef ; Hrubeš, Jan (referee) ; Kozumplík, Jiří (advisor)
Signal compression is daily-used tool for memory capacities reduction and for fast data communication. Methods based on wavelet transform seem to be very effective nowadays. Signal decomposition with a suitable bank filters following with coefficients quantization represents one of the available technique. After packing quantized coefficients into one sequence, run length coding together with Huffman coding are implemented. This thesis focuses on compression effectiveness for the different wavelet transform and quantization settings.
|
|
|
Image Compression Using the Wavelet Transform
Kontra, Matúš ; Drábek, Vladimír (referee) ; Bařina, David (advisor)
Wavelet transform belongs to modern methods used to compress data. It's application modifies data in such way, that we can use and store them in much more efficient way. Focus of this thesis lies in theoretical basis required to understand this method and its implementation. Next section shifts focus to quantization and coding - operations used to further reduce size of our data, which are provided by the SPIHT algorithm.
|
|
|
Image Compression Using the Wavelet Transform
Urbánek, Pavel ; Polok, Lukáš (referee) ; Bařina, David (advisor)
This thesis is focused on subject of image compression using wavelet transform. The first part of this document provides reader with information about image compression, presents well known contemporary algorithms and looks into details of wavelet compression and following encoding schemes. Both JPEG and JPEG 2000 standards are introduced. Second part of this document analyzes and describes implementation of image compression tool including inovations and optimalizations. The third part is dedicated to comparison and evaluation of achievements.
|
|
|
Advanced objective measurement criteria applied to image compression
Šimek, Josef ; Průša, Zdeněk (referee) ; Malý, Jan (advisor)
This diploma thesis deals with the problem of using an objective quality assessment methods in image data compression. Lossy compression always introduces some kind of distortion into the processed data causing degradation in the quality of the image. The intensity of this distortion can be measured using subjective or objective methods. To be able to optimize compression algorithms the objective criteria are used. In this work the SSIM index as a useful tool for describing the quality of compressed images has been presented. Lossy compression scheme is realized using the wavelet transform and SPIHT algorithm. The modification of this algorithm using partitioning of the wavelet coefficients into the separate tree-preserving blocks followed by independent coding, which is especially suitable for parallel processing, was implemented. For the given compression ratio the traditional problem is being solved – how to allocate available bits among the spatial blocks to achieve the highest possible image quality. The possible approaches to achieve this solution were discussed. As a result, some methods for bit allocation based on MSSIM index were proposed. To test the effectivity of these methods the MATLAB environment was used.
|
|
|
Image Compression Using the Wavelet Transform
Bradáč, Václav ; Polok, Lukáš (referee) ; Bařina, David (advisor)
This work deals with image compression using wavelet transformation. At the beginning , you can find theoretical information about the best known techniques used for image compression , a thorough description of wavelet transormation and the EBCOT algorithm. A significant part of the work is devoted to the library's own implementation . Another chapter of the diploma thesis deals with the comparison and evaluation of the achieved results of the processed library with the JPEG2000 format
|
|
|
Compression of ECG signals recorded using mobile ECG device
Had, Filip ; Vítek, Martin (referee) ; Němcová, Andrea (advisor)
Signal compression is necessary part for ECG scanning, because of relatively big amount of data, which must be transmitted primarily wirelessly for analysis. Because of the wireless sending it is necessary to minimize the amount of data as much as possible. To minimize the amount of data, lossless or lossy compression algorithms are used. This work describes an algorithm SPITH and newly created experimental method, based on PNG, and their testing. This master’s thesis there is also a bank of ECG signals with parallel sensed accelerometer data. In the last part, modification of SPIHT algorithm, which uses accelerometer data, is described and realized.
|
guest ::
