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Update DataGuide_AAPF_HSI.md
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oh231 authored Jun 28, 2024
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Expand Up @@ -93,15 +93,20 @@ The definition of column headers and corresponding values mostly originates from
| `scan_order` | The 'Scan order' column assigns a unique integer value to each scan incrementally based on the order of image capture during the experiment within the AAPF. This value is identical for all cameras (VNIR-SIDE, VNIR-TOP, SWIR-SIDE, and SWIR-TOP) operating concurrently during a single scanning session, which captures data for the same plant on the same day |
| `dark white` | "Dark" or "White", only available for `header_summary_ref.csv` |

### How to Read Animated GIF Files Containing VNIR-SWIR Coregistration Quality Info
### Interpretation of Animated GIF Files for VNIR-SWIR Coregistration Quality Assessment


| Side view | Top-down view |
|--------------------------------|-------------------------------------------------------------------------------------------------|
| <img src="https://github.itap.purdue.edu/PlantScience/DataExploration-AAPF/blob/main/resources/REG_SIDE.gif" width="480" height="360" /> | <img src="https://github.itap.purdue.edu/PlantScience/DataExploration-AAPF/blob/main/resources/REG_TOP.gif" width="480" height="360" /> |
|(1/4 frame) |

This section details the interpretation of an animated GIF file used to evaluate the coregistration quality between VNIR (visible and near-infrared) and SWIR (short-wave infrared) imagery. The animation consists of four frames, each displaying a vegetation mask derived from a specific processing step:


- Frame 1 (1/4): Vegetation mask obtained from the VNIR data (presented upside-down to match the original data orientation for both side and top-down views).
- Frame 2 (2/4): Vegetation mask derived from the SWIR data after an initial coarse alignment using affine transformation parameters (translation, scaling, and rotation) specified in [HSI data processing parameters](https://github.itap.purdue.edu/PlantScience/Pipeline-AAPF-HSI/blob/master/vardata_aapf_hsi.py).
Frame 3 (3/4): Vegetation mask from the SWIR data following a subsequent geometric refinement using the [cv.findTransformECC](https://amroamroamro.github.io/mexopencv/matlab/cv.findTransformECC.html) function. Significant misalignment between Frame 3 and Frame 4 may indicate the need to adjust the translation, scaling, and rotation parameters within [HSI data processing parameters](https://github.itap.purdue.edu/PlantScience/Pipeline-AAPF-HSI/blob/master/vardata_aapf_hsi.py).
Frame 4 (4/4): The vegetation mask from Frame 1 with an additional morphological filter applied. The "default" parameter applies no filtering, while "upper," "middle," and "lower" parameters utilize only the upper, middle, or lower third of the plant segments, respectively (applicable to side view images only). Future iterations may incorporate additional morphological filter options.


### How to Read Information in Spreadsheet file (.xlsx, masterfile)
Expand All @@ -122,6 +127,6 @@ The spreadsheets contains various phenotypic measurements derived from the HSI d
| `SCAN_TIME` | Scan start time |
| `SCAN_DATE` | Scan start date |
| `DFP` | Age of plant in days from planting at time of imaging |
| `{vegetation index}_{statistic}`<br>(e.g., NDVI_avg)| Vegetation index (VI) statistics within masked vegetation areas<br>[List of vegetation indices used](/resources/VI.md)<br>List of statistics: avg (average), sd(standard deviation), max, min, p## (##-th percentile) |
| `{vegetation index}_{statistic}`<br>(e.g., NDVI_avg)| Vegetation index (VI) statistics within masked vegetation areas<br>[List of vegetation indices](/resources/VI.md)<br>List of statistics: avg (average), sd(standard deviation), max, min, p## (##-th percentile) |
| `Wavelength in nm`<br>(e.g., 402.8)| Average reflectance over vegetation mask area (ratio of reflected energy to incident energy) |

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