scholarly journals Scaling and discriminability of perceived gloss

2020 ◽  
Author(s):  
Jacob Raleigh Cheeseman ◽  
James A. Ferwerda ◽  
Frank J. Maile ◽  
Roland Fleming
Keyword(s):  
Maximum Likelihood ◽  
Visual Sensitivity ◽  
Surface Reflectance ◽  
Natural Illumination ◽  
Specular Reflectance ◽  
Reflectance Model ◽  
Perceptual Scale ◽  
Method Of Constant Stimuli

While much attention has been given to understanding biases in gloss perception (e.g., changes in perceived reflectance as a function of lighting, shape, viewpoint and other factors), here we investigated sensitivity to changes in surface reflectance. We tested how visual sensitivity to differences in specular reflectance varies as a function of the magnitude of specular reflectance. Stimuli consisted of renderings of glossy objects under natural illumination. Using Maximum Likelihood Difference Scaling, we created a perceptual scaling of the specular reflectance parameter of the Ward reflectance model. Then, using the Method of Constant Stimuli and a standard 2AFC procedure, we obtained psychometric functions for gloss discrimination across a range of reflectance values derived from the perceptual scale. Both methods demonstrate that discriminability is significantly diminished at high levels of specular reflectance, suggesting that gloss sensitivity depends on the magnitude of change in the image produced by different reflectance values.

scholarly journals Surface reflectance estimation under unknown natural illumination

2010 ◽  
Vol 1 (3) ◽  
pp. 43-43 ◽  
Author(s):  
R. W. Fleming ◽  
R. O. Dror ◽  
E. H. Adelson
Keyword(s):  
Surface Reflectance ◽  
Natural Illumination

BOREAS RSS-01 PARABOLA SSA SURFACE REFLECTANCE AND TRANSMITTANCE DATA

1999 ◽  
Author(s):  
S. P. AHMAD ◽  
D. W. DEERING ◽  
T. F. ECK ◽  
E. M. MIDDLETON
Keyword(s):  
Surface Reflectance

PEMETAAN SEBARAN PADANG LAMUN MENGGUNAKAN CITRA SATELIT LANDSAT 8 DI KEPULAUAN TANIMBAR KABUPATEN MALUKU TENGGARA BARAT PROVINSI MALUKU

2019 ◽  
Vol 3 ◽  
pp. 871
Author(s):  
Desita Anggraeni ◽  
M. Nurkholis Fauzi ◽  
Christian Novia Ngesti H.
Keyword(s):  
Landsat 8 ◽  
Surface Reflectance ◽  
Halophila Ovalis ◽  
Halodule Uninervis ◽  
Gap Data

Padang lamun merupakan habitat penting pesisir yang memiliki peran kunci dalam ekosistem pesisir. Kawasan ini merupakan area asuhan bagi ikan-ikan kecil, udang, persembunyian biota dari predatornya, pendaur zat hara, serta penyerap nutrien dari limpasan air laut yang dapat membantu menstabilkan sedimen dan kejernihan air. Kepulauan Tanimbar merupakan salah satu lokasi di Provinsi Maluku dengan potensi sebaran lamun yang cukup luas, namun informasi mengenai sebaran lamun di kawasan ini tidak terdata dengan baik. Teknologi penginderaan jauh merupakan salah satu alternatif untuk mengisi gap data di area yang luas dan sulit dijangkau, termasuk untuk memetakan sebaran lamun di Kepulauan Tanimbar. Penelitian ini bertujuan untuk menyediakan data dasar sebaran dan luas habitat lamun di pesisir Kepulauan Tanimbar. Metode yang digunakan adalah analisis citra penginderaan jauh Landsat 8, menerapkan penajaman citra untuk perairan dangkal menggunakan algoritma Lyzenga. Citra Landsat yang digunakan Landsat Surface Reflectance liputan path/row 106/65 dan 106/66 tahun perekaman 2017. Pengambilan data lapangan dilakukan pada tanggal 1-10 November 2017. Metode pengambilan data lamun dilakukan menggunakan metode seagrass watch . Hasil pengolahan citra menunjukkan lamun terdistribusi merata di seluruh pesisir Kepulauan Tanimbar dengan luas total 5.615,63 hektar dengan tutupan terpadat di sekitar Pulau Seira. Hasil survei lapangan menunjukkan tutupan lamun terpadat dijumpai di Formusan dengan tutupan lamun rata-rata 95%. Kondisi lamun paling baik berada di daerah Sabal, didukung kondisi air yang sangat jernih dengan substrat utama pasir. Berdasarkan hasil pengamatan lapangan, jenis lamun yang ditemukan antara lain: E n h alu s a c o r oid e s , T h ala s sia h e m p ric hii, C y m o d o c e a s e r r ula t a , C y m o d o c e a rotundata, Syringodi um isoetifolium, Halodule uninervis, Halophila ovalis, dan Halophila minor .

scholarly journals iCOR Atmospheric Correction on Sentinel-3/OLCI over Land: Intercomparison with AERONET, RadCalNet, and SYN Level-2

2021 ◽  
Vol 13 (4) ◽  
pp. 654
Author(s):  
Erwin Wolters ◽  
Carolien Toté ◽  
Sindy Sterckx ◽  
Stefan Adriaensen ◽  
Claire Henocq ◽  
...  
Keyword(s):  
Optical Thickness ◽  
Vegetation Indices ◽  
Atmospheric Correction ◽  
Negative Bias ◽  
Surface Reflectance ◽  
Temporal Consistency ◽  
Correction Algorithm ◽  
Land Surfaces ◽  
Relative Differences ◽  
Level 2

To validate the iCOR atmospheric correction algorithm applied to the Sentinel-3 Ocean and Land Color Instrument (OLCI), Top-of-Atmosphere (TOA) observations over land, globally retrieved Aerosol Optical Thickness (AOT), Top-of-Canopy (TOC) reflectance, and Vegetation Indices (VIs) were intercompared with (i) AERONET AOT and AERONET-based TOC reflectance simulations, (ii) RadCalNet surface reflectance observations, and (iii) SYN Level 2 (L2) AOT, TOC reflectance, and VIs. The results reveal that, overall, iCOR’s statistical and temporal consistency is high. iCOR AOT retrievals overestimate relative to AERONET, but less than SYN L2. iCOR and SYN L2 TOC reflectances exhibit a negative bias of ~−0.01 and −0.02, respectively, in the Blue bands compared to the simulations. This diminishes for RED and NIR, except for a +0.02 bias for SYN L2 in the NIR. The intercomparison with RadCalNet shows relative differences < ±6%, except for bands Oa02 (Blue) and Oa21 (NIR), which is likely related to the reported OLCI “excess of brightness”. The intercomparison between iCOR and SYN L2 showed R2 = 0.80–0.93 and R2 = 0.92–0.96 for TOC reflectance and VIs, respectively. iCOR’s higher temporal smoothness compared to SYN L2 does not propagate into a significantly higher smoothness for TOC reflectance and VIs. Altogether, we conclude that iCOR is well suitable to retrieve statistically and temporally consistent AOT, TOC reflectance, and VIs over land surfaces from Sentinel-3/OLCI observations.

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