1. 概述

主要閱讀的文章包括：

• Ma, L., et al. 2019. Deep learning in remote sensing applications: A meta-analysis and review. Isprs Journal of Photogrammetry Remote Sensing, 152, 166-177.【高引780】
• Minaee, S., et al. 2021. Image segmentation using deep learning: A survey. IEEE Transactions on Pattern Analysis Machine Intelligence.【高引666】
• Kotaridis, I. and Lazaridou, M. 2021. Remote sensing image segmentation advances: A meta-analysis. Isprs Journal of Photogrammetry Remote Sensing, 173, 309-322.【應用17】

2. Ma, L., et al. 2019. Deep learning in remote sensing applications: A meta-analysis and review. Isprs Journal of Photogrammetry Remote Sensing, 152, 166-177.

文章出發點

前人聚焦在了一些relatively uncommon sub-areas of the remote sensing field，然而忽略了more common sub-areas。
Zhu et al. (2017) performed a broader review than others, but they focused on some relatively uncommon sub-areas of the remote sensing field (e.g., 3D modeling applications) while ignoring many other deserving (and more common) sub-areas; e.g., image classification applications.
所以一篇更定量化、更綜合的系統性文章需要形成。
A more systematic (i.e. quantitative) analysis is necessary to get a comprehensive and objective understanding of the applications of DL for remote-sensing analysis.

2.1 文章整體結構

algorithmic networks

• the supervised CNN
• recurrent neural network (RNN) models
• unsupervised autoencoders (AE)
• deep belief networks (DBN) models
• generative adversarial networks (GAN) model
• restricted Boltzmann machine (RBM)

主流期刊與會議

remote sensing image analysis tasks including

• image fusion
  Aim to obtain an image that simultaneously has high spectral and spatial resolutions.
  ① MS and PAN image fusion (pan-sharpening) which indicates the fusion of a low-resolution multi-spectral (MS) image and a high-resolution panchromatic (PAN) image to achieve a high-resolution MS image（pan-sharpening將原始的多光譜(MS)圖像和全色(PAN)圖像進行融合獲得高分辨率多光譜圖像的一種方法）。
  其他參考：https://blog.csdn.net/weixin_42166578/article/details/104238088
  ② HS and MS image fusion method
  ③ HS and MS image fusion method
• image registration
  Image registration is a method of aligning two or more images captured by different sensors, at different times or from different viewpoints (Zitova & Flusser, 2003; Ye et al., 2017).
  多源圖像間在幾何上是相互配準的，多源遙感圖像之間的同名點的確定是圖像配準的關鍵。
• scene classification
  In this study, scene classification is defined as a procedure to determine the image categories from numerous pictures—for example, agricultural scenes, forest scenes, and beach scenes (Zou et al., 2015)—and the training samples are a series of labeled pictures.
• object detection
  Object detection aims to detect different objects in a single image scene — for example, airplanes (Zhong et al., 2018), cars (Ding et al., 2018), and urban villages (Li et al., 2017b) — and the training samples are the pixels in a fixed-sized window or patch.
  難點
  Therefore, how to design the effective algorithms to overcome the difficulties emerging from different-scale objects (the different type of objects often appears at different scales in remote-sensing images, and also the same object can have variable size in different-scale remotesensing images) is an urgent problem in both subfields (Deng et al., 2018).
• use and land cover (LULC) classification,
• segmentation,
• object-based image analysis (OBIA).
  

2.2 專業詞匯

• hyper-spectral (HS) image
• multi-spectral (MS) image
• high-resolution panchromatic (PAN) image
• 樣本增強
  generate augmented data
  augmentation techniques
  Yu et al. (2017) applied three operations (flip, translation, and rotation) to generate augmented data and obtain a more descriptive deep model by using these augmented data as training data.
• UVA影像的超高分辨率特征
  ultra-high-resolution characteristics of unmanned aerial vehicles (UAVs)
• 具有地理標識的照片
  geotagged photos
• 具有識別能力的目標函數
  a new discriminative objective function
• 遙感數據集體量
  the volumes of available remote-sensing datasets
• 高分遙感場景分類
  VHR remote sensing scene classification
• 子領域
  subfield

2.3 精句

• 場景分類的高精度特性是優勢之一
  For example, typically the application of a scene classification technique to the accuracy assessment of remotesensing image classification is advantageous, as pointed out by Xing et al. (2018b).
• 降低人力，適用于大范圍區域
  This method can significantly reduce the complexity and labor required for the conventional validation process, particularly for the validation of classification results of land cover within the given scope of a large area.
• 很多研究更傾向于目標檢測研究而不是場景分類研究
  As mentioned above, we found that current studies preferred to extract certain specific type(s) of objects (airplanes, cars, etc.) from high-resolution images through a fixed window size, either through scene classification.
• 洪水、鹽堿化、干旱、人為建設、地質災害對耕地的保護帶來了巨大的沖擊。
  salinity and drought threats

2.4 模糊概念

3. Minaee, S., et al. 2021. Image segmentation using deep learning: A survey. IEEE Transactions on Pattern Analysis Machine Intelligence

3.1 文章整體結構

3.2 關鍵詞

3.3 關鍵句

3.4 模糊概念

4. Kotaridis, I. and Lazaridou, M. 2021. Remote sensing image segmentation advances: A meta-analysis. Isprs Journal of Photogrammetry Remote Sensing, 173, 309-322.

4.1 文章整體結構

• segmentation algorithm
  

• the software utilized
  

• the data source
  https://github.com/chinawindofmay/PaddleRS/blob/develop/docs/data/dataset_summary.md

4.2 關鍵詞

4.3 關鍵句

• OBIA includes two principal steps, image segmentation and object classification.
• 地理學第一定律在遙感領域同樣也是適用的
  This statement makes sense if we consider the first law of Geography, ’Everything is related to everything else. But near things are more related than distant things.’, that was established by Tobler in 1969. This idea applies to numerous phenomena, including
  remote sensing applications.
• Image segmentation 的起源和發展與3種分類（同質分割、連接分割、圖形分割）
  Image segmentation is not new, considering that it was established in the 1980 s and 1990s, with various segmentation algorithms available (Thenkabail, 2015). Segmentation algorithms are based on three fundamental criteria to cluster pixels into groups: the homogeneity within a segment, the differentiation from adjoining segments and shape homogeneity (Nussbaum and Menz, 2008).
• 影像分割的定義
  A common image analysis target of image segmentation is to successfully partition a remote sensing imagery into distinct earth surface regions and produce a labelled map.

4.4 模糊概念

總結

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