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Data · dataset · 2026

LMIF: A Large-scale Multi-focus Image Fusion Dataset Based on Smartphones

Listed in ScienceDB

Description

In reality, due to the limitations of optical lens depth of field, the images captured by the imaging system only have clear imaging within the depth of field range, and the imaging is blurry outside the depth of field range, making it difficult to focus all targets in the same shooting environment in a single photographic image. Therefore, multi-focus image fusion technology has significant research significance. With the rapid development of technology and the popularization of smartphones mobile phones have become the most convenient and widely used photography tool.

At present, the public multi focus data set is mostly collected by professional equipment, which cannot well reflect the photo effect of mobile phones in real environment, so this paper uses devices that are more suitable for real environments to construct multi-focus image datasets based on mobile phones. The dataset was collected from different models of mobile phones and covers most of the mobile phone brands on the market today.

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In the process of data acquisition, jitter and environmental light will inevitably occur, and at the same time, the collected data will also have the problem of excessive resolution, which is not conducive to the fusion work, so this paper preprocesses the collected data. The dataset is currently divided into three parts: A (containing 66 pairs of images), B (containing 63 pairs of images) and C (containing 100 pairs of images).

The dataset contains two parts: unprocessed data and preprocessed data. 

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Catalogue records · 1

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Inferred from text
Image 75% · Imaging 75%
Provenance · 1 source records, 11 field assertions
SourceKeyLast seenRaw
ScienceDB10.57760/sciencedb.435879 d agoJSON v1
FieldAssertionExtractorEvidence
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concepts[field].local:field:social-sciencemapping · scidb cnconnector:scidb_cn@1.0.0
concepts[modality].local:modality:imageenrichment · scidb cnkeyword-concept-rules@1.0.0title+description (75%)
concepts[modality].local:modality:imagingenrichment · scidb cnkeyword-concept-rules@1.0.0title+description (75%)
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