Content security protection for remote sensing images integrating selective content encryption and digital fingerprint

Xu, Yinghui; Wang, Chao; Zhang, Yuxia

doi:10.1117/1.jrs.6.063505

Cited by 7 publications

(4 citation statements)

References 12 publications

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“…In the scheme proposed by Xu et al [8], watermarking and encryption are combined, and the watermark is embedded in the image at the time of decryption of the image. One of the major problems of this scheme is that the encrypted image does not carry watermark.…”

Section: Introductionmentioning

confidence: 99%

Secure Dissemination and Protection of Raster Data using Merkle Hash Tree based Cryptowatermarking

Chaudhari

2020

ITM Web Conf.

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Due to rapid development in the Internet and other communication technologies, it becomes quite easy to copy and distribute multiple illegal copies of high value and sensitive data. Raster data is one of the high voluminous data and it requires huge efforts to sense and generate this data. Therefore, ownership protection as well as its integrity become one of the key problems in spatial information service. There are lot many schemes are available for watermarking and encryption individually, but if both are combined gives manifold advantages. This paper presents a cryptowatermarking scheme by combining watermarking and encryption to protect the copyright of raster data as well as to provide security dissemination level. We have proposed a scheme by employing double transposition, LSB substitution watermarking and Merkle Hash Tree for encryption and watermarking. It has been observed that the proposed scheme is not only robust against encryption attacks, but also has transparency, strongness, large data hiding capacity and correct extraction of watermark.

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Section: Introductionmentioning

confidence: 99%

Secure Dissemination and Protection of Raster Data using Merkle Hash Tree based Cryptowatermarking

Chaudhari

2020

ITM Web Conf.

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“…The SPAD meter measures the difference between the transmittance of a red and an infrared light [50]. Due to the strong correlation between chlorophyll content and SPAD values, measuring leaf SPAD values is an effective, non-destructive method for monitoring chlorophyll content in leaves [51]. The sample plants and measuring times used for determining leaf SPAD are the same as those used for LA.…”

Section: Experimental Designmentioning

confidence: 99%

Biochar Improves Greenhouse Tomato Yield: Source–Sink Relations under Deficit Irrigation

Li,

Zheng,

2023

Agronomy

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It is important to evaluate any effects that biochar may have on tomato yield under deficit-irrigation to develop water-saving and yield-increasing best management practices for greenhouse tomato production. For this purpose, greenhouse trials were conducted in 2021 and 2022 with five biochar (B) application rates and three irrigation (W) levels. The B treatments were B0: 0 t ha−1; B1: 15 t ha−1; B2: 30 t ha−1; B3: 45 t ha−1; and B4: 60 t ha−1, and the W levels were W1: 50–70% of field capacity (θf); W2: 60–80% of θf; and W3B0: 70–90% of θf full irrigation without biochar, which was designated as the control. Our objective was to quantify the effects of biochar on the characteristics of tomato sources and sinks to determine, first, the optimal irrigation–biochar combination to achieve high yield tomato production, and, second, evaluate the mechanisms of this effect. At W1 and W2 irrigation levels, the addition of 30–60 t ha−1 and 45–60 t ha−1 biochar could compensate for the adverse effects of deficit-irrigation on the tomato source and sink characteristics. Our results show that in both years the highest tomato yield was obtained with the W2 irrigation level and the B3 biochar application rate, with 52% higher tomato yield compared to the lowest value obtained with the W1 irrigation level and B0 application rate. We conclude that biochar application can improve tomato yield by promoting the filling rather than the building of the sink capacity. The tomato yield was mainly affected by the net photosynthetic rate (Pn), followed by the leaf area, and the leaf chlorophyll content indirectly affected tomato yield through Pn. The W2 irrigation level combined with the B3 biochar application rate resulted in the best water–biochar combination under the experimental conditions.

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“…Efficient and non-destructive monitoring of crop growth is the core of modern precision agriculture planting [8]. Due to the strong correlation between chlorophyll content and SPAD values, measuring leaf SPAD values is an effective, non-destructive method for monitoring chlorophyll content in leaves [9]. Currently, methods for manually measuring leaf SPAD values face problems such as a small measurement area, large workload, and poor data representativeness [10], which cannot meet the needs of large-scale and precise management of field maize.…”

Section: Introductionmentioning

confidence: 99%

Study on Monitoring SPAD Values for Multispatial Spatial Vertical Scales of Summer Maize Based on UAV Multispectral Remote Sensing

Cui

et al. 2023

Agriculture

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Rapid acquisition of chlorophyll content in maize leaves is of great significance for timely monitoring of maize plant health and guiding field management. In order to accurately detect the relative chlorophyll content of summer maize and study the responsiveness of vegetation indices to SPAD (soil and plant analyzer development) values of summer maize at different spatial vertical scales, this paper established a prediction model for SPAD values of summer maize leaves at different spatial scales based on UAV multispectral images. The experiment collected multispectral image data from summer maize at the jointing stage and selected eight vegetation indices. By using the sparrow search optimized kernel limit learning machine (SSA-KELM), the prediction models for canopy leaf (CL) SPADCL and ear leaf (EL) SPADEL were established, and a linear fitting analysis was conducted combining the measured SPADCL values and SPADEL values on the ground. The results showed that for SPADCL, the R2 of the linear fitting between the predicted values and measured values was 0.899, and the RMSE was 1.068. For SPADEL, the R2 of linear fitting between the predicted values and the measured values was 0.837, and the RMSE was 0.89. Compared with the model established by the partial least squares method (PLSR), it is found that the sparrow search optimized kernel limit learning machine (SSA-KELM) has more precise prediction results with better stability and adaptability for small sample prediction. The research results can provide technical support for remote sensing monitoring of the chlorophyll content of summer maize at different spatial scales.

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Content security protection for remote sensing images integrating selective content encryption and digital fingerprint

Cited by 7 publications

References 12 publications

Secure Dissemination and Protection of Raster Data using Merkle Hash Tree based Cryptowatermarking

Secure Dissemination and Protection of Raster Data using Merkle Hash Tree based Cryptowatermarking

Biochar Improves Greenhouse Tomato Yield: Source–Sink Relations under Deficit Irrigation

Study on Monitoring SPAD Values for Multispatial Spatial Vertical Scales of Summer Maize Based on UAV Multispectral Remote Sensing

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