Image Enrichment Using Single Discrete Wavelet Transform Multi-resolution and Frequency Partition

Mohan, Chinnem Rama; Kiran, S.

doi:10.1007/978-981-10-7868-2_9

Cited by 5 publications

(3 citation statements)

References 4 publications

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“…Mohan and Kiran 14 presented the concept of DWT for image fusion. Kant et al 15 presented the concept of wavelet transform based on local correlation-based fusion strategy for the enhancement of image details.…”

Section: Related Workmentioning

confidence: 99%

An efficient JPEG image compression based on Haar wavelet transform, discrete cosine transform, and run length encoding techniques for advanced manufacturing processes

Khan

Nazir

Hussain

et al. 2019

Measurement and Control

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Image compression plays a key role in the transmission of an image and storage capacity. Image compression aims to reduce the size of the image with no loss of significant information and no loss of quality in the image. To reduce the storage capacity of the image, the image compression is proposed in order to offer a compact illustration of the information included in the image. Image compression exists in the form of lossy or lossless. Even though image compression mechanism has a prominent role for compressing images, certain conflicts still exist in the available techniques. This paper presents an approach of Haar wavelet transform, discrete cosine transforms, and run length encoding techniques for advanced manufacturing processes with high image compression rates. These techniques work by converting an image (signal) into half of its length which is known as “detail levels”; then, the compression process is done. For simulation purposes of the proposed research, the images are segmented into 8 × 8 blocks and then inversed (decoded) operation is performed on the processed 8 × 8 block to reconstruct the original image. The same experiments were done on two other algorithms, that is, discrete cosine transform and run length encoding schemes. The proposed system is tested by comparing the results of all the three algorithms based on different images. The comparison among these techniques is drawn on the basis of peak signal to noise ratio and compression ratio. The results obtained from the experiments show that the Haar wavelet transform outperforms very well with an accuracy of 97.8% and speeds up the compression and decompression process of the image with no loss of information and quality of image. The proposed study can easily be implemented in industries for the compression of images. These compressed images are suggested for multiple purposes like image compression for metrology as measurement materials in advanced manufacturing processes, low storage and bandwidth requirements, and compressing multimedia data like audio and video formats.

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Section: Related Workmentioning

confidence: 99%

An efficient JPEG image compression based on Haar wavelet transform, discrete cosine transform, and run length encoding techniques for advanced manufacturing processes

Khan

Nazir

Hussain

et al. 2019

Measurement and Control

View full text Add to dashboard Cite

show abstract

“…The present paper evaluates twelve objective metrics to understand the performance of the proposed algorithm. [31,[33][34][35][36][37][38][39][40][41][42][43].…”

Section: Quality Metrics Of the Image Fusion Algorithmmentioning

confidence: 99%

Advanced Multifocus Image Fusion algorithm using FPDCT with Modified PCA

Mohan¹,

Kiran²,

Kumar³

2019

IJITEE

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 Abstract: Image fusion has been performed and reported in this paper for multi-focused images using Frequency Partition Discrete Cosine Transform (FP-DCT) with Modified Principal component analysis (MPCA) technique. The image fusion with decomposition at fixed levels may be treated as a very critical rule in the earlier image processing techniques. The frequency partitioning approach was used in this study to select the decomposition levels based on the pixel intensity and clarity. This paper also presents the modified PCA technique which provides dimensionality reduction. The wide range of quality evaluation metrics was computed to compare the fusion performance on the five images. Different techniques such as PCA, wavelet transforms with PCA, Multiresolution Singular Value Decomposition (MSVD) with PCA, Multiresolution DCT (MRDCT) with PCA, Frequency partitioning DCT (FP-DCT) with PCA were computed for comparison with the proposed FP-DCT Modified PCA (MPCA) technique. Images obtained after fusion process obtained by the method proposed shows enhanced visual quality, negligible information loss and discontinuities in the image than compared to other state of the art methods.

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“…A number of papers have been published late on the development of various pixel image fusion algorithms. Many algorithms are based on transform wavelets [16][17], pyramids transform [ 18 ], statistic signal processing [ 19 ], principal component analysis [ 16,19,29 ], fuzzy logic [ 20,25 ], DCT [ 15,[21][22] portioning [ 23,28 ], etc. DCT has been shown to be well for image compression and is well received in several applications of image preprocessing.…”

Section: Introductionmentioning

confidence: 99%

Image Enhancement based on Fusion using 2D LPDCT and Modified PCA

2019

IJEAT

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The images play a vital role in various fields of applications; medical field is the one, where images more widely used in diagnosis. Best image data analysis results if the quality of the image is high. To attain best image quality some popular techniques are available, among that image fusion is one of the technique, it enhances the information of the image by selecting and merging the significant information from two or more similar multi-focus images. Using the features of image fusion a new technique is proposed in this paper. In proposed technique, fusion of sources images with 2D Laplacian Pyramid Discrete Cosine Transformation (2D LP - DCT) and Modified Principal Component Analysis (MPCA). In this, two similar multi-focus images are considered, first, they undergone to 2D LP-DCT and then MPCA technique. The 2D LP-DCT enhances important image features, which are best utilized in image fusion and results good image quality. In Modified PCA, the concept of dimensionality reduction is used. The experimental results indicate that the suggested strategy can produce fused images with good visual quality and computational effectiveness than other state-of-the-art works.

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Image Enrichment Using Single Discrete Wavelet Transform Multi-resolution and Frequency Partition

Cited by 5 publications

References 4 publications

An efficient JPEG image compression based on Haar wavelet transform, discrete cosine transform, and run length encoding techniques for advanced manufacturing processes

An efficient JPEG image compression based on Haar wavelet transform, discrete cosine transform, and run length encoding techniques for advanced manufacturing processes

Advanced Multifocus Image Fusion algorithm using FPDCT with Modified PCA

Image Enhancement based on Fusion using 2D LPDCT and Modified PCA

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