https://projectswiki.eleceng.adelaide.edu.au/projects/api.php?action=feedcontributions&feedformat=atom&user=A1789660 2026-04-24T17:35:06Z User contributions MediaWiki 1.31.4 https://projectswiki.eleceng.adelaide.edu.au/projects/index.php?title=Projects:2020s2-7233_Image_Denoising_with_Dictionaries&diff=15117 2020-09-14T12:59:30Z

<p>A1789660: </p> <hr /> <div>== Abstract ==<br /> Image denoising is essential phase in the pre-processing of images. Different algorithms have been proposed in the past few decades with varying denoising capabilities. K-Singular Value Decomposition (K-SVD) algorithm is currently the most widely used adaptive learning dictionary in image denosing problem. In this study, K-SVD algorithm will be implemented in image denoising and observe the performance when using different image datasets. <br /> == Introduction ==<br /> Dictionary learning is a topical area of signal processing research. It shares similarities but also crucial differences from other machine learning ideas such as deep learning neural networks. It rests on the idea of sparse representations using a well-designed dictionary that can lead to high performance in a wide range of signal processing applications. Image denoising is one of many signal processing applications. The idea developed here can easily be transferred to other application area.<br /> === Project Team ===<br /> ==== Project Students ====<br /> * Muhammad Haziq Saharuddin<br /> * Muhammad Faizal Azhar<br /> * Chen Chen<br /> ==== Project Supervisor ====<br /> * Associate Professor Brian Ng<br /> === Objectives ===<br /> * To analyse performance of dictionary learning on various image datasets<br /> * To implement K-SVD method image denoising <br /> * To evaluate the effectiveness of different matching pursuit of algorithms in dictionary learning</div>

A1789660 https://projectswiki.eleceng.adelaide.edu.au/projects/index.php?title=Projects:2020s2-7233_Image_Denoising_with_Dictionaries&diff=15116 2020-09-14T12:26:57Z

<p>A1789660: </p> <hr /> <div>== Abstract ==<br /> Image denoising is essential phase in the pre-processing of images. Different algorithms have been proposed in the past few decades with varying denoising capabilities. K-Singular Value Decomposition algorithm is currently the most widely used adaptive learning dictionary in image denosing problem. <br /> == Introduction ==<br /> Dictionary learning is a topical area of signal processing research. It shares similarities but also crucial differences from other machine learning ideas such as deep learning neural networks. It rests on the idea of sparse representations using a well-designed dictionary that can lead to high performance in a wide range of signal processing applications. Image denoising is one of many signal processing applications. The idea developed here can easily be transferred to other application area.<br /> === Project Team ===<br /> ==== Project Students ====<br /> * Muhammad Haziq Saharuddin<br /> * Muhammad Faizal Azhar<br /> * Chen Chen<br /> ==== Project Supervisor ====<br /> * Associate Professor Brian Ng<br /> === Objectives ===<br /> * To analyse performance of dictionary learning on various image datasets<br /> * To implement K-SVD method image denoising <br /> * To test the effectiveness of different matching pursuit of algorithms in dictionary learning</div>

A1789660 https://projectswiki.eleceng.adelaide.edu.au/projects/index.php?title=Projects:2020s2-7233_Image_Denoising_with_Dictionaries&diff=15113 2020-09-14T12:04:21Z

<p>A1789660: </p> <hr /> <div>== Abstract ==<br /> <br /> == Introduction ==<br /> Dictionary learning is a topical area of signal processing research. It shares similarities but also crucial differences from other machine learning ideas such as deep learning neural networks. It rests on the idea of sparse representations using a well-designed dictionary that can lead to high performance in a wide range of signal processing applications. Image denoising is one of many signal processing applications. The idea developed here can easily be transferred to other application area.<br /> === Project Team ===<br /> ==== Project Students ====<br /> * Muhammad Haziq Saharuddin<br /> * Muhammad Faizal Azhar<br /> * Chen Chen<br /> ==== Project Supervisor ====<br /> * Associate Professor Brian Ng<br /> === Objectives ===<br /> * To analyse performance of dictionary learning on various image datasets<br /> * To implement K-SVD method image denoising <br /> * To test the effectiveness of different matching pursuit of algorithms in dictionary learning</div>

A1789660 https://projectswiki.eleceng.adelaide.edu.au/projects/index.php?title=Projects:2020s2-7233_Image_Denoising_with_Dictionaries&diff=15112 2020-09-14T12:01:27Z

<p>A1789660: </p> <hr /> <div>== Abstract ==<br /> <br /> == Introduction ==<br /> Dictionary learning is a topical area of signal processing research. It shares similarities but also crucial differences from other machine learning ideas such as deep learning neural networks. It rests on the idea of sparse representations using a well-designed dictionary that can lead to high performance in a wide range of signal processing applications. Image denoising is one of many signal processing applications. The idea developed here can easily be transferred to other application area.<br /> == Project Team ==<br /> === Project Students ===<br /> * Muhammad Haziq Saharuddin<br /> * Muhammad Faizal Azhar<br /> * Chen Chen<br /> === Project Supervisor ===<br /> * Associate Professor Brian Ng<br /> === Objectives ===<br /> * To analyse performance of dictionary learning on various image datasets<br /> * To implement K-SVD method image denoising <br /> * To test the effectiveness of different matching pursuit of algorithms in dictionary learning</div>

A1789660 https://projectswiki.eleceng.adelaide.edu.au/projects/index.php?title=Projects:2020s2-7233_Image_Denoising_with_Dictionaries&diff=15110 2020-09-14T11:59:46Z

<p>A1789660: </p> <hr /> <div>== Abstract ==<br /> <br /> == Introduction ==<br /> Dictionary learning is a topical area of signal processing research. It shares similarities but also crucial differences from other machine learning ideas such as deep learning neural networks. It rests on the idea of sparse representations using a well-designed dictionary that can lead to high performance in a wide range of signal processing applications. Image denoising is one of many signal processing applications. The idea developed here can easily be transferred to other application area.<br /> == Project Team ==<br /> === Project Students ===<br /> * Muhammad Haziq Saharuddin<br /> * Muhammad Faizal Azhar<br /> * Chen Chen<br /> === Project Supervisor ===<br /> * Associate Professor Brian Ng<br /> == Objectives ==<br /> * To analyse performance of dictionary learning on various image datasets<br /> * To implement K-SVD method image denoising <br /> * To test the effectiveness of different matching pursuit of algorithms in dictionary learning</div>

A1789660 https://projectswiki.eleceng.adelaide.edu.au/projects/index.php?title=Projects:2020s2-7233_Image_Denoising_with_Dictionaries&diff=15109 2020-09-14T11:55:14Z

<p>A1789660: </p> <hr /> <div>== Abstract ==<br /> <br /> == Introduction ==<br /> Dictionary learning is a topical area of signal processing research. It shares similarities but also crucial differences from other machine learning ideas such as deep learning neural networks. It rests on the idea of sparse representations using a well-designed dictionary that can lead to high performance in a wide range of signal processing applications. Image denoising is one of many signal processing applications. The idea developed here can easily be transferred to other application area.<br /> == Project Team ==<br /> === Project Students ===<br /> * Muhammad Haziq Saharuddin<br /> * Muhammad Faizal Azhar<br /> * Chen Chen<br /> === Project Supervisor ===<br /> * Associate Professor Brian Ng<br /> == Objectives ==</div>

A1789660 https://projectswiki.eleceng.adelaide.edu.au/projects/index.php?title=Projects:2020s2-7233_Image_Denoising_with_Dictionaries&diff=15108 2020-09-14T11:47:49Z

<p>A1789660: </p> <hr /> <div>== Abstract ==<br /> hello<br /> == Introduction ==<br /> <br /> == Project Team ==<br /> === Project Students ===<br /> * Muhammad Haziq Saharuddin<br /> * Muhammad Faizal Azhar<br /> * Chen Chen<br /> === Project Supervisor ===<br /> * Associate Professor Brian Ng<br /> == Objectives ==</div>

A1789660 https://projectswiki.eleceng.adelaide.edu.au/projects/index.php?title=Projects:2020s2-7233_Image_Denoising_with_Dictionaries&diff=15107 2020-09-14T11:46:32Z

<p>A1789660: </p> <hr /> <div>== Abstract ==<br /> hello<br /> == Introduction ==<br /> <br /> == Project Team ==<br /> === Project Students ===<br /> * Muhammad Haziq Saharuddin<br /> * Muhammad Faizal Azhar<br /> * Chen Chen<br /> === Project Supervisor ===<br /> == Objectives ==</div>

A1789660 https://projectswiki.eleceng.adelaide.edu.au/projects/index.php?title=Projects:2020s2-7233_Image_Denoising_with_Dictionaries&diff=15106 2020-09-14T11:45:22Z

<p>A1789660: </p> <hr /> <div>== Abstract ==<br /> hello<br /> == Introduction ==<br /> <br /> == Project Team ==<br /> === Project Students ===<br /> === Project Supervisor ===<br /> == Objectives ==</div>

A1789660 https://projectswiki.eleceng.adelaide.edu.au/projects/index.php?title=Projects:2020s2-7233_Image_Denoising_with_Dictionaries&diff=15105 2020-09-14T11:43:42Z

<p>A1789660: </p> <hr /> <div>== Abstract ==<br /> hello<br /> == Introduction ==<br /> <br /> == Project Team ==</div>

A1789660 https://projectswiki.eleceng.adelaide.edu.au/projects/index.php?title=Projects:2020s2-7233_Image_Denoising_with_Dictionaries&diff=15104 2020-09-14T11:41:51Z

<p>A1789660: Created page with &quot;Abstract Introduction Project Team&quot;</p> <hr /> <div>Abstract<br /> <br /> Introduction<br /> <br /> Project Team</div>

A1789660