Hyperspectral Image Lossless Compression Method Based on Band Correlation Adjustment

Yunhan Long; Fan Yang; Haoping Zhang; Kehao Chi; Fengxiang Wang; Genghua Huang; Buhua Tu; Congfeng Liu

doi:10.3788/AOS250538

Acta Optica Sinica, Volume. 45, Issue 12, 1230002(2025)

Hyperspectral Image Lossless Compression Method Based on Band Correlation Adjustment

Yunhan Long^1,2, Fan Yang³, Haoping Zhang³, Kehao Chi^2,3,4, Fengxiang Wang^3,4, Genghua Huang^1,2,3,4, Buhua Tu^2,3, and Congfeng Liu^2,3、*

Author Affiliations

¹Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, Zhejiang , China

²University of Chinese Academy of Sciences, Beijing 100049, China

³Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China

⁴Key Laboratory of Space Active Optical-Electro Technology, CAS, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China

show less

Abstract Get PDF(in Chinese)

Figures & Tables(16)

Fig. 1. Flowchart of CCSDS-123-B-2 algorithm

Download full size

Fig. 2. Schematic of prediction window

Download full size

Fig. 3. Comparison of band-to-band correlation coefficients. (a) Band 30 of Indian Pines; (b) band 80 of Indian Pines

Download full size

Fig. 4. Flowchart of the proposed algorithm

Download full size

Fig. 5. Schematic diagram of reference band adjustment method based on band correlation

Download full size

Fig. 6. Flowchart of reference band adjustment method based on band correlation

Download full size

Fig. 7. Multispectral experimental samples. (a) Landsat_agriculture; (b) Modis_A2001222.0835day; (c) Modis_A2001123.0000day; (d) Modis_A2001222.1200night

Download full size

Fig. 8. Hyperspectral experimental samples. (a) Indian Pines; (b) YellowstoneUn_Sc00; (c) Hawaii_Sc01; (d) Maine_Sc10

Download full size

Fig. 9. Comparison of hyperspectral data compression ratio and band correlation coefficient. (a) Band 8 of Indian Pines; (b) band 40 of Indian Pines

Download full size

Fig. 10. Comparison of compression performance under different t_h and t settings

Download full size

Fig. 11. Comparison of bit rate between original CCSDS-123-B-2 algorithm and proposed method. (a) Indian Pines dataset; (b) Hawaii_Sc01 dataset

Download full size

Fig. 12. Correlation between adjacent bands. (a) Landsat_agriculture dataset; (b) YellowstoneUn_Sc00 dataset

Download full size

Table 1. Image specifications of multispectral datasets

View table

Table 1. Image specifications of multispectral datasets

Type	Landsat_agriculture	Modis_A2001222.0835day	Modis_A2001123.0000day	Modis_A2001222.1200night
Sensor	Lansat 8	MODIS	MODIS	MODIS
Wavelength range /μm	0.435‒12.51	0.4‒14	0.4‒14	0.4‒14
Number of bands	6	14	14	17
Spatial dimension	1024×1024	1354×2030	1354×2030	1354×2030
Bit depth	8	12	12	12

Table 2. Image specifications of hyperspectral datasets

View table

Table 2. Image specifications of hyperspectral datasets

Type	Indian Pines	YellowstoneUn_Sc00	Hawaii_Sc01	Maine_Sc10
Sensor	AVIRIS	AVIRIS	AVIRIS	AVIRIS
Wavelength range /μm	0.41‒2.45	0.41‒2.45	0.41‒2.45	0.41‒2.45
Number of bands	220	224	224	224
Spatial dimension	145×145	512×680	512×680	512×680
Bit depth	12	16	12	12

Table 3. Comparison of compression performance under different t_h and h settings

View table

Table 3. Comparison of compression performance under different t_h and h settings

Parameter set	t_h=0.025	t_h=0.021	t_h=0.019	t_h=0.015	t_h=0.010	t_h=0.005	t_h=0.001
t=0.5	6.8414	6.8341	6.8341	6.8260	6.8246	6.8056	6.7728
t=0.6	6.8412	6.8338	6.8338	6.8258	6.8244	6.8054	6.8054
t=0.7	6.8051	6.8438	6.8438	6.8358	6.8344	6.8154	6.7826
t=0.8	6.8631	6.8558	6.8557	6.8478	6.8463	6.8274	6.7945

Table 4. Compression performance of different datasets under various compression algorithms

View table

Table 4. Compression performance of different datasets under various compression algorithms

Spectrum type	Dataset type	Dataset	Bit rate /（bit/pixel）
Spectrum type	Dataset type	Dataset	JPEG-LS	Original CCSDS-123-B-2	BRCCBH+CCSDS-123-B-2	Proposed method
Hyperspectral data	R	Indian Pines	7.9904	6.9651	6.9594	6.7728
	T	YellowstoneUn_Sc00	7.1512	6.8401	6.8325	6.7359
		Hawaii_Sc01	3.2722	3.0741	3.0613	2.9927
		Maine_Sc10	3.3629	3.1199	3.1106	3.0610
Multispectral data	R	Modis_A2001222.0835day	7.5482	7.3771	7.2198	7.2334
	T	Modis_A2001123.0000day	5.4429	5.1003	4.9565	4.9424
		Modis_A2001222.1200night	6.7995	6.6706	6.5652	6.5700
		Landsat_agriculture	4.6193	4.1328	3.9331	3.9506
Average			5.7733	5.4100	5.3298	5.2823

Tools

Get Citation

Copy Citation Text

Yunhan Long, Fan Yang, Haoping Zhang, Kehao Chi, Fengxiang Wang, Genghua Huang, Buhua Tu, Congfeng Liu. Hyperspectral Image Lossless Compression Method Based on Band Correlation Adjustment[J]. Acta Optica Sinica, 2025, 45(12): 1230002

Download Citation

EndNote(RIS)BibTex Plain Text

Set citation alerts for article

Save article for my favorites

Paper Information

Category: Spectroscopy

Received: Jan. 24, 2025

Accepted: Apr. 3, 2025

Published Online: Jun. 24, 2025

The Author Email: Congfeng Liu (cfliu@mail.sitp.ac.cn)

DOI:10.3788/AOS250538

CSTR:32393.14.AOS250538

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology

Table 1. Image specifications of multispectral datasets

Table 1. Image specifications of multispectral datasets

Table 2. Image specifications of hyperspectral datasets

Table 2. Image specifications of hyperspectral datasets

Table 3. Comparison of compression performance under different th and h settings

Table 3. Comparison of compression performance under different th and h settings

Table 4. Compression performance of different datasets under various compression algorithms

Table 4. Compression performance of different datasets under various compression algorithms

Table 3. Comparison of compression performance under different t_h and h settings

Table 3. Comparison of compression performance under different t_h and h settings