Aerial Photography Vehicle Removal

27 Feb 2024 - 5 min read
accuracy of vehicle identification
reduction in manual cost
90% +
increase in image processing speed
increase in applications


With the widespread adoption of aerial photography technology, capturing the world from a high vantage point has become a new pathway for enthusiasts and professionals alike. However, these aerial images are often obscured by vehicles on the ground, affecting the display of original roads and natural scenery, thereby impacting the overall aesthetics and accuracy of the images.

This not only prevents the images from accurately reflecting the city's road planning and landscape design but also reduces the visual appeal of the images. To address this issue, an innovative technology—Aerial Photography Vehicle Removal—has been introduced.

Technical Highlights

1. Object Detection Technology

From a bird's-eye view, our technology can identify a wide variety of vehicles with astonishing precision, ranging from large construction vehicles to everyday cars, as well as lightweight motorcycles and small vehicles. This object detection technology utilizes advanced algorithms to ensure accurate identification of each vehicle, even in the busiest streets or most complex environments.

2. Image Infilling Technology

Utilizing the most advanced deep learning techniques for image infilling, we can automatically and swiftly repair and fill in images without the need for laborious manual work. This technology can understand and mimic the textures and details of the surrounding environment, realistically filling in the gaps left by removed objects. Whether it's urban roads or natural landscapes, we can restore the integrity and beauty of the images with incredible speed and precision, presenting a flawless visual experience.

Challenges Faced

In the aspect of object identification, we face a significant challenge. Traditionally, object identification technology often deals with objects in larger-sized everyday photos, where vehicle images usually present ample detail. However, in the realm of aerial photography, the size of vehicles can be as small as 30 to 50 pixels, sometimes even smaller. This size reduction significantly increases the difficulty of identification, as the loss of detail may lead to a decrease in identification accuracy.

Moreover, specific challenges in aerial images include the appearance of building decorations and monochromatic objects on roads, which may sometimes be confused with vehicles, leading to misidentification by the system. To overcome these difficulties, we have taken a series of measures to enhance our technology. We have collected a large amount of aerial imagery from various heights and areas, specifically for deep training in object identification. This enables our system to identify vehicles with greater accuracy, even when the vehicles are smaller or in complex backgrounds.

For objects that are not vehicles but are prone to misidentification, our advanced image-infilling technology can intervene. By understanding the textures and details of the surrounding environment, it can accurately repair and fill these areas. Thus, even when facing intricate identification challenges, we can ensure that the final images presented to users achieve a natural and flawless effect.


The Aerial Photography Vehicle Removal technology, by integrating advanced deep learning algorithms with aerial photography, can precisely identify vehicles in high-altitude images and remove them, thereby achieving the purpose of beautifying and purifying aerial images. The application of this technology not only restores the original beauty of urban and natural landscapes but also provides clear and flawless visual resources for fields such as city planning, landscape design, and map updating. By removing visual obstacles, we can present a cityscape free from vehicle obstruction, offering viewers a pure and harmonious perspective. This not only enhances the visual experience of high-altitude images but also opens up new possibilities for various fields, allowing us to rediscover the beauty of the world from a fresh perspective.

1. Enhancing Visual Aesthetics

Removing vehicles from aerial images significantly improves the overall aesthetics of the images, allowing the originally obscured roads and natural scenery to be displayed.

2. Increasing Accuracy

Images with vehicles removed more accurately reflect the city's road planning and landscape design, providing valuable visual data for fields such as urban planning and traffic management.

3. Facilitating Field Applications

Clear and flawless aerial images have important applications in city planning, landscape design, map updating, and other fields, helping to improve work efficiency and decision-making quality.

4. Improving Identification Accuracy

By training on a large amount of aerial imagery from different heights and areas, we have significantly improved the accuracy of vehicle identification, even in complex backgrounds.

5. Reducing the Need for Manual Repairs

Advanced image infilling technology can automatically repair and fill in areas left blank by removing vehicles, saving time and costs without extensive manual intervention.

6. Providing a Pure Perspective

Through technological processing, we offer viewers a cityscape unobstructed by vehicles, more natural and harmonious, enhancing the viewing experience.

7. Opening New Possibilities

The advancement of technology not only improves the quality of aerial images but also opens new possibilities for research and applications in related fields, allowing us to discover the beauty of the world from a new angle.

Data-Driven Achievements

Accuracy Improvement

Through the application of deep learning and object detection technologies, the accuracy of vehicle identification has been improved to over 95%, significantly reducing false positives and omissions.

Image Processing Speed

Utilizing advanced image inpainting technology, the processing time for each image has been reduced from several hours to a few minutes, greatly enhancing work efficiency.

Reduced Manual Repair Needs

Automated image processing technology has reduced the need for manual repairs by about 80%, saving a substantial amount of time and labor costs.

Enhanced 3D Model Quality

After vehicle removal, the quality of images used for 3D modeling has significantly improved, leading to more accurate and detailed Digital Surface Models (DSM) and road evaluation results.

Expanded Application Areas

The purified high-quality aerial images have expanded the application range in urban planning, traffic management, and landscape design by 30%, providing more accurate and comprehensive data support.

Find out more about Vehicle Removal in our catalog!