diff --git a/app/service/design_pre_processing/service.py b/app/service/design_pre_processing/service.py
index 7a3974a..4c55997 100644
--- a/app/service/design_pre_processing/service.py
+++ b/app/service/design_pre_processing/service.py
@@ -58,7 +58,21 @@ class DesignPreprocessing:
             if len(image.shape) == 2:
                 image = cv2.cvtColor(image, cv2.COLOR_GRAY2RGB)
             elif image.shape[2] == 4:  # 如果是四通道 mask
-                image = image[:, :, :3]
+                # 分离RGB和Alpha通道
+                bgr = image[:, :, :3]
+                alpha = image[:, :, 3]
+
+                # 创建白色背景（也可改为其他颜色，如(255,255,255)就是白色）
+                background_color = (255, 255, 255)
+                background = np.full_like(bgr, background_color)
+
+                # 将Alpha通道转换为掩码（0=透明，255=不透明）
+                alpha_mask = alpha / 255.0  # 归一化到0-1
+                alpha_mask = np.expand_dims(alpha_mask, axis=-1)  # 扩展维度，方便广播计算
+
+                # 混合背景和原图：透明区域显示背景色，不透明区域显示原图
+                image = (bgr * alpha_mask + background * (1 - alpha_mask)).astype(np.uint8)
+                # 此时image已经是3通道RGB，无需再执行image = image[:, :, :3]
             obj["image_obj"] = image
         return image_list
 
@@ -174,8 +188,9 @@ class DesignPreprocessing:
             scale = 0.4
             if waist_width / scale >= image_width:
                 add_width = int((waist_width / scale - image_width) / 2)
-                ret = cv2.copyMakeBorder(image['obj'], 0, 0, add_width, add_width, cv2.BORDER_CONSTANT, value=(256, 256, 256))
-                image_bytes = cv2.imencode(".jpg", ret)[1].tobytes()
+                ret = cv2.copyMakeBorder(image['obj'], 0, 0, add_width, add_width, cv2.BORDER_CONSTANT, value=(255, 255, 255))
+                img_rgba = cv2.cvtColor(ret, cv2.COLOR_RGB2RGBA)
+                image_bytes = cv2.imencode(".png", img_rgba)[1].tobytes()
                 # image['show_image_url'] = f"{image['image_url'].split('/', 1)[0]}/{self.minio_client.put_object(image['image_url'].split('/', 1)[0], image['image_url'].split('/', 1)[1].replace('.', '-show.'), io.BytesIO(image_bytes), len(image_bytes), content_type='image/jpeg').object_name}"
                 bucket_name = image['image_url'].split('/', 1)[0]
                 object_name = image['image_url'].split('/', 1)[1].replace('.', '-show.')