Nano Banana Pro: Managing Lens Flare Artifacts Through Glass with Mixed Lights

When generating images that simulate a view through a window or glass partition, users often encounter unexpected visual noise known as lens flare artifacts. This issue becomes particularly pronounced when the scene involves mixed interior lighting conditions interacting with a simulated glass surface. Instead of a clear transmission of light, the image may display streaks, ghosting, or hazy halos that obscure the intended subject matter. These artifacts are not merely aesthetic flaws; they can fundamentally alter the mood of the composition, making a cozy interior look chaotic or a professional setting appear unpolished.

The symptom typically manifests as bright, diffuse shapes that do not correspond to any physical object in the scene description. They often appear near high-contrast edges where the interior lights meet the glass boundary. In some cases, these flares may look like reflections of the camera itself or strange geometric patterns caused by the interaction of multiple light sources. It is crucial to distinguish between intentional artistic glows and these specific artifacts. Intentional glows usually have a defined source and direction, whereas unwanted artifacts tend to scatter randomly or create a uniform haze that reduces image clarity.

Separating Plausible Causes from Known Technical Facts

To effectively troubleshoot this issue, it is necessary to separate plausible user assumptions from the verified capabilities of the tool. A common misconception is that these artifacts are caused by a lack of realism in the rendering engine or a failure to simulate physical optics accurately. While real-world cameras produce lens flare due to internal reflections within lens elements, AI image generation models operate on pattern recognition and synthesis rather than physical ray tracing.

Verified facts indicate that Nano Banana Pro, identified as Gemini 3 Pro Image, is designed to handle complex prompts and multi-turn editing. However, the model does not guarantee identity, label, object, or typography preservation in every instance. This means that when a prompt asks for a specific lighting setup, the model might interpret "mixed interior lights" in ways that generate unintended optical effects. The presence of these artifacts is often a result of the model's interpretation of conflicting visual cues rather than a hardware limitation or a bug in the software.

It is important to note that while Google documents Nano Banana Pro as a distinct model focused on higher fidelity, the website does not claim that all features are identical across different versions or that the tool functions exactly like a physical camera. Users should avoid assuming that the tool will automatically correct for optical physics unless explicitly prompted to do so. The artifact generation is a byproduct of the text-to-image workflow where the model attempts to reconcile the concept of "glass" with "bright lights" without a predefined physical constraint.

Diagnosing the Prompt Structure for Clean Transmission

Diagnosing the root cause usually involves analyzing the specific wording used in the prompt. If the prompt relies heavily on adjectives like "glowing," "bright," or "luminous" without specifying the behavior of the glass, the model may default to generating flare-like textures. The issue often stems from a lack of negative constraints regarding the transparency of the glass. When the prompt describes the interior lights but fails to explicitly state that the glass should be "clean" or "transparent," the model fills the gap with visual noise.

Furthermore, the complexity of the lighting setup plays a significant role. Mixed interior lights imply varying color temperatures and intensities. If the prompt does not clarify how these lights interact with the glass plane, the model might blend them in a way that creates artificial halos. The diagnosis should focus on whether the prompt clearly distinguishes between the light source inside the room and the medium (glass) through which it is viewed. Without this distinction, the model treats the light and the glass as a single entity, leading to the observed artifacts.

Fixing the Issue with Targeted Prompt Engineering

Resolving lens flare artifacts requires a strategic approach to prompt engineering that prioritizes clarity and separation of elements. To fix this, users should explicitly instruct the model to maintain clean transmission through the glass. This can be achieved by adding specific descriptors such as "crystal clear glass," "unobstructed view," or "no reflections." By defining the properties of the glass, the model is guided to render the surface as a transparent barrier rather than an active participant in the lighting effect.

Additionally, users should refine the description of the interior lights. Instead of simply stating "mixed lights," specify the arrangement and intensity. For example, "soft ambient lighting with no direct glare on the glass" helps the model understand the desired outcome. It is also beneficial to use negative prompting if the interface supports it, explicitly excluding terms like "flare," "haze," or "ghosting." This directs the model away from generating the unwanted artifacts.

For those seeking to experiment with these techniques, you can Try Nano Banana to test how different phrasing affects the final output. Remember that prompt instructions describe desired outcomes but do not guarantee identity or perfect preservation of every detail. Therefore, iterative refinement is key. Start with a base prompt describing the scene, then layer in constraints about the glass clarity and light behavior until the artifacts disappear.

Verifying Results and Ensuring Consistency

After applying the revised prompt, verification is essential to ensure the artifacts have been removed without compromising the artistic intent. Users should inspect the generated image for any residual streaks or hazy areas around the light sources. If the image still shows signs of flare, further adjustments to the prompt may be necessary, perhaps by increasing the emphasis on the transparency of the glass or reducing the intensity of the light descriptions.

It is also important to verify that the glow of the lights has been preserved. The goal is to remove the unwanted artifacts while maintaining the atmospheric quality of the scene. If the image looks too sterile or flat, the prompt may have over-corrected by removing all light interactions. In such cases, reintroduce subtle descriptors like "warm glow" or "soft diffusion" to restore the ambiance without triggering the flare artifacts again.

By following these steps, users can effectively manage lens flare artifacts in Nano Banana Pro, achieving clean, professional-looking images that accurately represent the intended lighting scenario. This process highlights the importance of precise communication with the AI model to overcome the limitations of its generative nature.