Signal compression and enhancement using a new orthogonal-polynomial-based discrete transform
Discrete orthogonal functions are important tools in digital signal processing. These functions received considerable attention in the last few decades. This study proposes a new set of orthogonal functions called discrete Krawtchouk-Tchebichef transform (DKTT). Two traditional orthogonal polynomial...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
The Institution of Engineering and Technology
2017
|
| Online Access: | http://psasir.upm.edu.my/id/eprint/63212/1/Signal%20compression%20and%20enhancement%20using%20a%20new%20orthogonal-polynomial-based%20discrete%20transform.pdf |
| _version_ | 1825932566083928064 |
|---|---|
| author | Mahmmod, Basheera M. Ramli, Abd Rahman Abdulhussain, Sadiq H. Al-Haddad, Syed Abdul Rahman Jassim, Wissam A. |
| author_facet | Mahmmod, Basheera M. Ramli, Abd Rahman Abdulhussain, Sadiq H. Al-Haddad, Syed Abdul Rahman Jassim, Wissam A. |
| author_sort | Mahmmod, Basheera M. |
| collection | UPM |
| description | Discrete orthogonal functions are important tools in digital signal processing. These functions received considerable attention in the last few decades. This study proposes a new set of orthogonal functions called discrete Krawtchouk-Tchebichef transform (DKTT). Two traditional orthogonal polynomials, namely, Krawtchouk and Tchebichef, are combined to form DKTT. The theoretical and mathematical frameworks of the proposed transform are provided. DKTT was tested using speech and image signals from a well-known database under clean and noisy environments. DKTT was applied in a speech enhancement algorithm to evaluate the efficient removal of noise from speech signal. The performance of DKTT was compared with that of standard transforms. Different types of distance (similarity index) and objective measures in terms of image quality, speech quality, and speech intelligibility assessments were used for comparison. Experimental tests show that DKTT exhibited remarkable achievements and excellent results in signal compression and speech enhancement. Therefore, DKTT can be considered as a new set of orthogonal functions for futuristic applications of signal processing. |
| first_indexed | 2024-03-06T09:43:59Z |
| format | Article |
| id | upm.eprints-63212 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T09:43:59Z |
| publishDate | 2017 |
| publisher | The Institution of Engineering and Technology |
| record_format | dspace |
| spelling | upm.eprints-632122018-08-20T06:24:36Z http://psasir.upm.edu.my/id/eprint/63212/ Signal compression and enhancement using a new orthogonal-polynomial-based discrete transform Mahmmod, Basheera M. Ramli, Abd Rahman Abdulhussain, Sadiq H. Al-Haddad, Syed Abdul Rahman Jassim, Wissam A. Discrete orthogonal functions are important tools in digital signal processing. These functions received considerable attention in the last few decades. This study proposes a new set of orthogonal functions called discrete Krawtchouk-Tchebichef transform (DKTT). Two traditional orthogonal polynomials, namely, Krawtchouk and Tchebichef, are combined to form DKTT. The theoretical and mathematical frameworks of the proposed transform are provided. DKTT was tested using speech and image signals from a well-known database under clean and noisy environments. DKTT was applied in a speech enhancement algorithm to evaluate the efficient removal of noise from speech signal. The performance of DKTT was compared with that of standard transforms. Different types of distance (similarity index) and objective measures in terms of image quality, speech quality, and speech intelligibility assessments were used for comparison. Experimental tests show that DKTT exhibited remarkable achievements and excellent results in signal compression and speech enhancement. Therefore, DKTT can be considered as a new set of orthogonal functions for futuristic applications of signal processing. The Institution of Engineering and Technology 2017-02 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/63212/1/Signal%20compression%20and%20enhancement%20using%20a%20new%20orthogonal-polynomial-based%20discrete%20transform.pdf Mahmmod, Basheera M. and Ramli, Abd Rahman and Abdulhussain, Sadiq H. and Al-Haddad, Syed Abdul Rahman and Jassim, Wissam A. (2017) Signal compression and enhancement using a new orthogonal-polynomial-based discrete transform. IET Signal Processing, 12 (1). pp. 129-142. ISSN 1751-9675; ESSN: 1751-9683 10.1049/iet-spr.2016.0449 |
| spellingShingle | Mahmmod, Basheera M. Ramli, Abd Rahman Abdulhussain, Sadiq H. Al-Haddad, Syed Abdul Rahman Jassim, Wissam A. Signal compression and enhancement using a new orthogonal-polynomial-based discrete transform |
| title | Signal compression and enhancement using a new orthogonal-polynomial-based discrete transform |
| title_full | Signal compression and enhancement using a new orthogonal-polynomial-based discrete transform |
| title_fullStr | Signal compression and enhancement using a new orthogonal-polynomial-based discrete transform |
| title_full_unstemmed | Signal compression and enhancement using a new orthogonal-polynomial-based discrete transform |
| title_short | Signal compression and enhancement using a new orthogonal-polynomial-based discrete transform |
| title_sort | signal compression and enhancement using a new orthogonal polynomial based discrete transform |
| url | http://psasir.upm.edu.my/id/eprint/63212/1/Signal%20compression%20and%20enhancement%20using%20a%20new%20orthogonal-polynomial-based%20discrete%20transform.pdf |
| work_keys_str_mv | AT mahmmodbasheeram signalcompressionandenhancementusinganeworthogonalpolynomialbaseddiscretetransform AT ramliabdrahman signalcompressionandenhancementusinganeworthogonalpolynomialbaseddiscretetransform AT abdulhussainsadiqh signalcompressionandenhancementusinganeworthogonalpolynomialbaseddiscretetransform AT alhaddadsyedabdulrahman signalcompressionandenhancementusinganeworthogonalpolynomialbaseddiscretetransform AT jassimwissama signalcompressionandenhancementusinganeworthogonalpolynomialbaseddiscretetransform |