Super Resolution of Wavelet-Encoded Images and Videos

In this dissertation, we address the multiframe super resolution reconstruction problem for wavelet-encoded images and videos. The goal of multiframe super resolution is to obtain one or more high resolution images by fusing a sequence of degraded or aliased low resolution images of the same scene. Since the low resolution images may be unaligned, a registration step is required before super resolution reconstruction. Therefore, we first explore in-band (i.e. in the wavelet-domain) image registration; then, investigate super resolution. Our motivation for analyzing the image registration and super resolution problems in the wavelet domain is the growing trend in wavelet-encoded imaging, and wavelet-encoding for image/video compression. Due to drawbacks of widely used discrete cosine transform in image and video compression, a considerable amount of literature is devoted to wavelet-based methods. However, since wavelets are shift-variant, existing methods cannot utilize wavelet subbands efficiently. In order to overcome this drawback, we establish and explore the direct relationship between the subbands under a translational shift, for image registration and super resolution. We then employ our devised in-band methodology, in a motion compensated video compression framework, to demonstrate the effective usage of wavelet subbands. Super resolution can also be used as a post-processing step in video compression in order to decrease the size of the video files to be compressed, with downsampling added as a pre-processing step. Therefore, we present a video compression scheme that utilizes super resolution to reconstruct the high frequency information lost during downsampling. In addition, super resolution is a crucial post-processing step for satellite imagery, due to the fact that it is hard to update imaging devices after a satellite is launched. Thus, we also demonstrate the usage of our devised methods in enhancing resolution of pansharpened multispectral images

Resolution enhancement of video sequences by using discrete wavelet transform and illumination compensation

This research paper proposes a new technique for video resolution enhancement that employees an illumination compensation procedure before the registration process. After the illumination compensation process, the respective frames are registered using the Irani and Peleg technique. In parallel, the corresponding frame is decomposed into high-frequency (low-high, high-low, and high-high) and low-frequency (low-low) subbands using discrete wavelet transform (DWT). The high-frequency subbands are superresolved using bicubic interpolation. Afterwards, the interpolated high-frequency subbands and superresolved low-frequency subband obtained by registration are used to construct the high-resolution frame using inverse DWT. The superiority of the proposed resolution enhancement method over well-known video superresolution techniques is shown with quantitative experimental results. For the Akiyo video sequence, there are improvements of 2.26 dB when compared to the average peak signal-to-noise ratio obtained by the state-of-the-art resolution technique proposed by Vandewalle

Satellite image resolution enhancement using discrete wavelet transform and new edge-directed interpolation

An image resolution enhancement approach based on discrete wavelet transform (DWT) and new edge-directed interpolation (NEDI) for degraded satellite images by geometric distortion to correct the errors in image geometry and recover the edge details of directional high-frequency subbands is proposed. The observed image is decomposed into four frequency subbands through DWT, and then the three high-frequency subbands and the observed image are processed with NEDI. To better preserve the edges and remove potential noise in the estimated high-frequency subbands, an adaptive threshold is applied to process the estimated wavelet coefficients. Finally, the enhanced image is reconstructed by applying inverse DWT. Four criteria are introduced, aiming to better assess the overall performance of the proposed approach for different types of satellite images. A public satellite images data set is selected for the validation purpose. The visual and quantitative results show the superiority of the proposed approach over the conventional and state-of-the-art image resolution enhancement

Wavelet-based image and video super-resolution reconstruction.

Super-resolution reconstruction process offers the solution to overcome the high-cost and inherent resolution limitations of current imaging systems. The wavelet transform is a powerful tool for super-resolution reconstruction. This research provides a detailed study of the wavelet-based super-resolution reconstruction process, and wavelet-based resolution enhancement process (with which it is closely associated). It was addressed to handle an explicit need for a robust wavelet-based method that guarantees efficient utilisation of the SR reconstruction problem in the wavelet-domain, which will lead to a consistent solution of this problem and improved performance. This research proposes a novel performance assessment approach to improve the performance of the existing wavelet-based image resolution enhancement techniques. The novel approach is based on identifying the factors that effectively influence on the performance of these techniques, and designing a novel optimal factor analysis (OFA) algorithm. A new wavelet-based image resolution enhancement method, based on discrete wavelet transform and new-edge directed interpolation (DWT-NEDI), and an adaptive thresholding process, has been developed. The DWT-NEDI algorithm aims to correct the geometric errors and remove the noise for degraded satellite images. A robust wavelet-based video super-resolution technique, based on global motion is developed by combining the DWT-NEDI method, with super-resolution reconstruction methods, in order to increase the spatial-resolution and remove the noise and aliasing artefacts. A new video super-resolution framework is designed using an adaptive local motion decomposition and wavelet transform reconstruction (ALMD-WTR). This is to address the challenge of the super-resolution problem for the real-world video sequences containing complex local motions. The results show that OFA approach improves the performance of the selected wavelet-based methods. The DWT-NEDI algorithm outperforms the state-of-the art wavelet-based algorithms. The global motion-based algorithm has the best performance over the super-resolution techniques, namely Keren and structure-adaptive normalised convolution methods. ALMD-WTR framework surpass the state-of-the-art wavelet-based algorithm, namely local motion-based video super-resolution.PhD in Manufacturin

Vedel-objektiiv abil salvestatud kaugseire piltide analüüs kasutades super-resolutsiooni meetodeid

Väitekirja elektrooniline versioon ei sisalda publikatsiooneKäesolevas doktoritöös uuriti nii riist- kui ka tarkvaralisi lahendusi piltide töötlemiseks. Riist¬varalise poole pealt pakuti lahenduseks uudset vedelläätse, milles on dielekt¬rilisest elastomeerist kihilise täituriga membraan otse optilisel teljel. Doktoritöö käigus arendati välja kaks prototüüpi kahe erineva dielektrilisest elastomeerist ki¬hilise täituriga, mille aktiivne ala oli ühel juhul 40 ja teisel 20 mm. Läätse töö vas¬tas elastomeeri deformatsiooni mehaanikale ja suhtelistele muutustele fookuskau¬guses. Muutuste demonstreerimiseks meniskis ja läätse fookuskauguse mõõtmiseks kasutati laserkiirt. Katseandmetest selgub, et muutuste tekitamiseks on vajalik pinge vahemikus 50 kuni 750 volti. Tarkvaralise poole pealt pakuti uut satelliitpiltide parandamise süsteemi. Paku¬tud süsteem jagas mürase sisendpildi DT-CWT laineteisenduse abil mitmeteks sagedusalamribadeks. Pärast müra eemaldamist LA-BSF funktsiooni abil suu¬rendati pildi resolutsiooni DWT-ga ja kõrgsagedusliku alamriba piltide interpo¬leerimisega. Interpoleerimise faktor algsele pildile oli pool sellest, mida kasutati kõrgsagedusliku alamriba piltide interpoleerimisel ning superresolutsiooniga pilt rekonst¬rueeriti IDWT abil. Käesolevas doktoritöös pakuti tarkvaraliseks lahenduseks uudset sõnastiku baasil töötavat super-resolutsiooni (SR) meetodit, milles luuakse paarid suure resolutsiooniga (HR) ja madala resolut-siooniga (LR) piltidest. Kõigepealt jagati vastava sõnastiku loomiseks HR ja LR paarid omakorda osadeks. Esialgse HR kujutise saamiseks LR sisendpildist kombineeriti HR osi. HR osad valiti sõnastikust nii, et neile vastavad LR osad oleksid võimalikult lähedased sisendiks olevale LR pil¬dile. Iga valitud HR osa heledust korrigeeriti, et vähendada kõrvuti asuvate osade heleduse erine¬vusi superresolutsiooniga pildil. Plokkide efekti vähendamiseks ar¬vutati saadud SR pildi keskmine ning bikuupinterpolatsiooni pilt. Lisaks pakuti käesolevas doktoritöös välja kernelid, mille tulemusel on võimalik saadud SR pilte teravamaks muuta. Pakutud kernelite tõhususe tõestamiseks kasutati [83] ja [50] poolt pakutud resolutsiooni parandamise meetodeid. Superreso¬lutsiooniga pilt saadi iga kerneli tehtud HR pildi kombineerimise teel alpha blen¬dingu meetodit kasutades. Pakutud meetodeid ja kerneleid võrreldi erinevate tavaliste ja kaasaegsete meetoditega. Kvantita-tiivsetest katseandmetest ja saadud piltide kvaliteedi visuaal¬sest hindamisest selgus, et pakutud meetodid on tavaliste kaasaegsete meetoditega võrreldes paremad.In this thesis, a study of both hardware and software solutions for image enhance¬ment has been done. On the hardware side, a new liquid lens design with a DESA membrane located directly in the optical path has been demonstrated. Two pro¬totypes with two different DESA, which have a 40 and 20 mm active area in diameter, were developed. The lens performance was consistent with the mechan¬ics of elastomer deformation and relative focal length changes. A laser beam was used to show the change in the meniscus and to measure the focal length of the lens. The experimental results demonstrate that voltage in the range of 50 to 750 V is required to create change in the meniscus. On the software side, a new satellite image enhancement system was proposed. The proposed technique decomposed the noisy input image into various frequency subbands by using DT-CWT. After removing the noise by applying the LA-BSF technique, its resolution was enhanced by employing DWT and interpolating the high-frequency subband images. An original image was interpolated with half of the interpolation factor used for interpolating the high-frequency subband images, and the super-resolved image was reconstructed by using IDWT. A novel single-image SR method based on a generating dictionary from pairs of HR and their corresponding LR images was proposed. Firstly, HR and LR pairs were divided into patches in order to make HR and LR dictionaries respectively. The initial HR representation of an input LR image was calculated by combining the HR patches. These HR patches are chosen from the HR dictionary corre-sponding to the LR patches that have the closest distance to the patches of the in¬put LR image. Each selected HR patch was processed further by passing through an illumination enhancement processing order to reduce the noticeable change of illumination between neighbor patches in the super-resolved image. In order to reduce the blocking effect, the average of the obtained SR image and the bicubic interpolated image was calculated. The new kernels for sampling have also been proposed. The kernels can improve the SR by resulting in a sharper image. In order to demonstrate the effectiveness of the proposed kernels, the techniques from [83] and [50] for resolution enhance¬ment were adopted. The super-resolved image was achieved by combining the HR images produced by each of the proposed kernels using the alpha blending tech-nique. The proposed techniques and kernels are compared with various conventional and state-of-the-art techniques, and the quantitative test results and visual results on the final image quality show the superiority of the proposed techniques and ker¬nels over conventional and state-of-art technique