Melarosa Cam ((new)) -

While effective, these systems impose constraints on form‑factor, power, and price that preclude widespread adoption in consumer‑grade devices (e.g., smartphones, wearables) and emerging markets. offers a promising alternative: by deliberately encoding scene information in the optical domain and decoding it with algorithms, one can trade modest optical complexity for powerful software reconstruction.

via deep learning (e.g., Monodepth2, Godard et al., ICCV , 2019) achieves impressive results but suffers from scale ambiguity and requires large training datasets. Hybrid optical‑computational schemes (e.g., Coded Aperture Camera for Depth (CADD) , Kim et al., TPAMI , 2021) mitigate this by embedding depth cues directly in the raw image, reducing the learning burden. melarosa cam

| Component | Specification | Rationale | |-----------|---------------|-----------| | | 4 mm focal length, f/1.8 aspheric glass | Provides sufficient light gathering while keeping the form factor compact. | | Phase Mask | 150 µm thick fused silica, grayscale diffractive pattern (pixel pitch = 2 µm) | Encodes depth into PSF shape; manufactured via electron‑beam lithography; anti‑reflective coating (AR < 1 %). | | Sensor | 12 MP (4000 × 3000) back‑illuminated CMOS, 1.1 µm pixel size, global shutter | High spatial resolution needed to capture fine PSF variations; low read‑out noise (≈ 1 e⁻). | | Mechanical Housing | 3‑D‑printed aluminum frame, total thickness 8 mm | Rigid alignment, thermal management. | Hybrid optical‑computational schemes (e