Increasing quality in fingerprint images by Implementing wavelet transform based fusion technique

Enesi, Indrit; Cico, Betim; Harizaj, Miranda

doi:10.1145/3472410.3472447

Cited by 1 publication

(1 citation statement)

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“…The local histogram equalization map can enhance the local details of the image but lacks global integrity. Wavelet transform [7], discrete wavelet transform [8], stationary wavelet transform [9] and other transform domain methods distinguish the basic information and detailed information of the image and perform multi-exposure image fusion. At present, the transform domain algorithm based on the wavelet transform can achieve the effect of enhancing the image [10].…”

Section: Related Workmentioning

confidence: 99%

Multi-Exposure Image Fusion based on Window Segmentation and a Laplacian Pyramid for Chip Package Appearance Quality Detection

Fei¹,

Song²,

Sun³

et al. 2022

IJACSA

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A heterogeneous material image enhancement method based on multi-exposure image fusion is proposed to address the problem of obtaining high-quality images from the single imaging of chips containing two extremely different reflectivity materials. First, a multi-exposure image fusion algorithm based on window segmentation and Laplacian pyramid fusion is proposed. Then, orthogonal experiments are used to optimize the parameters of the imaging system. Next, a method based on information entropy and average gray intensity is utilized to calculate the imaging exposure times of two heterogeneous materials, and two exposure time ranges are obtained that are appropriate for regions with high and low reflectivity. Finally, the subjective and objective experimental evaluations are conducted after the multi-exposure image set has been established. The results show that the fused image has a good visual effect, the information entropy is 6.29, and the average gray intensity is 131.56. In addition, time consumption is reduced by an average of 20.3% compared to the Laplace pyramid strategy. The heterogeneous material enhancement method based on multi-exposure image fusion proposed in this paper is effective and deserving of further research and application.

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Section: Related Workmentioning

confidence: 99%